Output processing.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b5993614",
   "metadata": {},
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: 'maxConvsBenign3.pkl'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[1], line 6\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mmatplotlib\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mpyplot\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mplt\u001b[39;00m\n\u001b[0;32m      4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[1;32m----> 6\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28;43mopen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mmaxConvsBenign3.pkl\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mrb\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m f:\n\u001b[0;32m      7\u001b[0m     benignNew \u001b[38;5;241m=\u001b[39m pickle\u001b[38;5;241m.\u001b[39mload(f)\n\u001b[0;32m      8\u001b[0m \u001b[38;5;66;03m#print(benign)\u001b[39;00m\n",
      "File \u001b[1;32m~\\AppData\\Local\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py:284\u001b[0m, in \u001b[0;36m_modified_open\u001b[1;34m(file, *args, **kwargs)\u001b[0m\n\u001b[0;32m    277\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m file \u001b[38;5;129;01min\u001b[39;00m {\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m2\u001b[39m}:\n\u001b[0;32m    278\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[0;32m    279\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mIPython won\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mt let you open fd=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfile\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m by default \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    280\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mas it is likely to crash IPython. If you know what you are doing, \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    281\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124myou can use builtins\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m open.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    282\u001b[0m     )\n\u001b[1;32m--> 284\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m io_open(file, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "\u001b[1;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'maxConvsBenign3.pkl'"
     ]
    }
   ],
   "source": [
    "import pickle\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "with open('maxConvsBenign3.pkl', 'rb') as f:\n",
    "    benignNew = pickle.load(f)\n",
    "#print(benign)\n",
    "\n",
    "with open('maxConvsMalicious3.pkl', 'rb') as f:\n",
    "    maliciousNew = pickle.load(f)\n",
    "#print(malicious)\n",
    "with open('maxConvsBenign4.pkl', 'rb') as f:\n",
    "    benignOld = pickle.load(f)\n",
    "#print(benign)\n",
    "\n",
    "with open('maxConvsMalicious4.pkl', 'rb') as f:\n",
    "    maliciousOld = pickle.load(f)\n",
    "#print(malicious)\n",
    "\n",
    "# Create a DataFrame with a column named \"anomaly score\"\n",
    "benignOld_df = pd.DataFrame({'anomaly score': benignOld})\n",
    "benignNew_df = pd.DataFrame({'anomaly score': benignNew})\n",
    "\n",
    "# Add the \"verdict\" column based on your condition\n",
    "benignOld_df['verdict'] = benignOld_df['anomaly score'].apply(lambda x: 'MALICIOUS' if x > 0.8 else 'BENIGN')\n",
    "benignNew_df['verdict'] = benignNew_df['anomaly score'].apply(lambda x: 'MALICIOUS' if x > 0.8 else 'BENIGN')\n",
    "\n",
    "# Print the statistics about the \"MALICIOUS\" entries\n",
    "#malicious_count = (benign_df['verdict'] == 'MALICIOUS').sum()\n",
    "#total_count = len(benign_df)\n",
    "#print(malicious_count)\n",
    "#print(malicious_count/total_count)\n",
    "benignNew_df.describe()\n",
    "plt.title('benign')\n",
    "plt.boxplot(np.log(benignOld_df['anomaly score']))\n",
    "plt.show()\n",
    "#benign_df['anomaly score'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0680f0fb",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'maliciousOld' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[2], line 2\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;66;03m# Create df with anomaly score column\u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m maliciousOld_df \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mDataFrame({\u001b[38;5;124m'\u001b[39m\u001b[38;5;124manomaly score\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[43mmaliciousOld\u001b[49m})\n\u001b[0;32m      3\u001b[0m maliciousNew_df \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mDataFrame({\u001b[38;5;124m'\u001b[39m\u001b[38;5;124manomaly score\u001b[39m\u001b[38;5;124m'\u001b[39m: maliciousNew})\n\u001b[0;32m      5\u001b[0m threshold \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0.0414269460152369\u001b[39m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'maliciousOld' is not defined"
     ]
    }
   ],
   "source": [
    "# Create df with anomaly score column\n",
    "maliciousOld_df = pd.DataFrame({'anomaly score': maliciousOld})\n",
    "maliciousNew_df = pd.DataFrame({'anomaly score': maliciousNew})\n",
    "\n",
    "threshold = 0.0414269460152369\n",
    "\n",
    "# Add the \"verdict\" column based on condition\n",
    "maliciousOld_df['verdict'] = maliciousOld_df['anomaly score'].apply(lambda x: 'MALICIOUS' if x > 0.8 else 'BENIGN')\n",
    "maliciousNew_df['verdict'] = maliciousNew_df['anomaly score'].apply(lambda x: 'MALICIOUS' if x > threshold else 'BENIGN')\n",
    "\n",
    "# Print the statistics about the \"MALICIOUS\" entries\n",
    "malicious_count = (maliciousOld_df['verdict'] == 'MALICIOUS').sum()\n",
    "total_count = len(maliciousOld_df)\n",
    "#print(malicious_count)\n",
    "#print(malicious_count/total_count)\n",
    "maliciousOld_df.describe()\n",
    "#plt.title('malicious')\n",
    "#plt.boxplot(np.log(malicious_df['anomaly score']))\n",
    "#plt.boxplot(np.log(benign_df['anomaly score']))\n",
    "\n",
    "#plt.show()\n",
    "maliciousOld_df['anomaly score'].describe()\n",
    "\n",
    "# Assuming you have the dataframes maliciousOld_df, maliciousNew_df, benignOld_df, and benignNew_df\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2)\n",
    "fig.suptitle('Anomaly scores')\n",
    "\n",
    "# Combine the data for maliciousOld and maliciousNew, and benignOld and benignNew\n",
    "malicious_data = [np.log(maliciousOld_df['anomaly score']), np.log(maliciousNew_df['anomaly score'])]\n",
    "benign_data = [np.log(benignOld_df['anomaly score']), np.log(benignNew_df['anomaly score'])]\n",
    "\n",
    "# Create two boxplots with different colors\n",
    "boxplot1 = ax1.boxplot(malicious_data, patch_artist=True, labels=['Old', 'New'])\n",
    "boxplot2 = ax2.boxplot(benign_data, patch_artist=True, labels=['Old', 'New'])\n",
    "\n",
    "# Set the fill colors for the boxes using RGB values\n",
    "malicious_colors = ['lightblue', 'lightgreen']\n",
    "benign_colors = ['lightpink', 'orange']  # Use valid RGB value for \"orange\"\n",
    "\n",
    "for patch, color in zip(boxplot1['boxes'], malicious_colors):\n",
    "    patch.set_facecolor(color)\n",
    "\n",
    "for patch, color in zip(boxplot2['boxes'], benign_colors):\n",
    "    patch.set_facecolor(color)\n",
    "\n",
    "# Set titles for the subplots\n",
    "ax1.set_title('Malicious')\n",
    "ax2.set_title('Benign')\n",
    "\n",
    "#plt.show()\n",
    "print(maliciousNew_df['verdict'])\n",
    "print(maliciousNew_df['verdict'].value_counts()/len(maliciousNew_df.index))\n",
    "\n",
    "\n",
    "print(benignNew_df['verdict'])\n",
    "print(benignNew_df['verdict'].value_counts()/len(benignNew_df.index))\n",
    "benignNew_df['anomaly score'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e3d0f371",
   "metadata": {},
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: 'seen.pkl'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[3], line 2\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;66;03m# Seen data, model trained on 360,000 packets and tested on 30,000 packets\u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28;43mopen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mseen.pkl\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mrb\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m f:\n\u001b[0;32m      3\u001b[0m     test \u001b[38;5;241m=\u001b[39m pickle\u001b[38;5;241m.\u001b[39mload(f)\n\u001b[0;32m      5\u001b[0m test_df \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mDataFrame({\u001b[38;5;124m'\u001b[39m\u001b[38;5;124manomaly score\u001b[39m\u001b[38;5;124m'\u001b[39m: test})\n",
      "File \u001b[1;32m~\\AppData\\Local\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py:284\u001b[0m, in \u001b[0;36m_modified_open\u001b[1;34m(file, *args, **kwargs)\u001b[0m\n\u001b[0;32m    277\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m file \u001b[38;5;129;01min\u001b[39;00m {\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m2\u001b[39m}:\n\u001b[0;32m    278\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[0;32m    279\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mIPython won\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mt let you open fd=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfile\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m by default \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    280\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mas it is likely to crash IPython. If you know what you are doing, \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    281\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124myou can use builtins\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m open.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    282\u001b[0m     )\n\u001b[1;32m--> 284\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m io_open(file, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "\u001b[1;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'seen.pkl'"
     ]
    }
   ],
   "source": [
    "# Seen data, model trained on 360,000 packets and tested on 30,000 packets\n",
    "with open('seen.pkl', 'rb') as f:\n",
    "    test = pickle.load(f)\n",
    "\n",
    "test_df = pd.DataFrame({'anomaly score': test})\n",
    "test_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3be2d1cb",
   "metadata": {},
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: 'unseen.pkl'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[4], line 2\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;66;03m# Seen data, model trained on 360,000 packets and tested on 30,000 packets\u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28;43mopen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43munseen.pkl\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mrb\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m f:\n\u001b[0;32m      3\u001b[0m     test \u001b[38;5;241m=\u001b[39m pickle\u001b[38;5;241m.\u001b[39mload(f)\n\u001b[0;32m      5\u001b[0m test_df \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mDataFrame({\u001b[38;5;124m'\u001b[39m\u001b[38;5;124manomaly score\u001b[39m\u001b[38;5;124m'\u001b[39m: test})\n",
      "File \u001b[1;32m~\\AppData\\Local\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py:284\u001b[0m, in \u001b[0;36m_modified_open\u001b[1;34m(file, *args, **kwargs)\u001b[0m\n\u001b[0;32m    277\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m file \u001b[38;5;129;01min\u001b[39;00m {\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m2\u001b[39m}:\n\u001b[0;32m    278\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[0;32m    279\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mIPython won\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mt let you open fd=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfile\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m by default \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    280\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mas it is likely to crash IPython. If you know what you are doing, \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    281\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124myou can use builtins\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m open.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    282\u001b[0m     )\n\u001b[1;32m--> 284\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m io_open(file, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "\u001b[1;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'unseen.pkl'"
     ]
    }
   ],
   "source": [
    "# Seen data, model trained on 360,000 packets and tested on 30,000 packets\n",
    "with open('unseen.pkl', 'rb') as f:\n",
    "    test = pickle.load(f)\n",
    "\n",
    "test_df = pd.DataFrame({'anomaly score': test})\n",
    "test_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "833094c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>anomaly score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>29999.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.032437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.047307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.002327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.005393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.009404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.043250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.221550</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       anomaly score\n",
       "count   29999.000000\n",
       "mean        0.032437\n",
       "std         0.047307\n",
       "min         0.002327\n",
       "25%         0.005393\n",
       "50%         0.009404\n",
       "75%         0.043250\n",
       "max         0.221550"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Unseen data, model trained on 360,000 packets and tested on 30,000 packets\n",
    "with open('tuesdaybenign30.pkl', 'rb') as f:\n",
    "    test = pickle.load(f)\n",
    "\n",
    "test_df = pd.DataFrame({'anomaly score': test})\n",
    "test_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5f7b70cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>anomaly score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>29999.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.013998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.039740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.002032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.002275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.002449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.002695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.318722</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       anomaly score\n",
       "count   29999.000000\n",
       "mean        0.013998\n",
       "std         0.039740\n",
       "min         0.002032\n",
       "25%         0.002275\n",
       "50%         0.002449\n",
       "75%         0.002695\n",
       "max         0.318722"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Unseen data, model trained on 360,000 packets and tested on 30,000 packets\n",
    "with open('tuesdaymalicious30.pkl', 'rb') as f:\n",
    "    test = pickle.load(f)\n",
    "\n",
    "test_df = pd.DataFrame({'anomaly score': test})\n",
    "test_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "17cd4917",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pickle\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "\n",
    "# Specify the directory where your pickle files are located\n",
    "directory = '.'  # Replace with the actual directory path\n",
    "\n",
    "# Initialize empty dataframes and a list to store attack types\n",
    "dfs = []\n",
    "attack_types = []\n",
    "\n",
    "# Loop through the files in the directory\n",
    "for filename in os.listdir(directory):\n",
    "    if filename.endswith(\".pkl\"):\n",
    "        # Parse the day and attack type from the filename\n",
    "        parts = filename.split(\"_\")\n",
    "        day = parts[0]\n",
    "        attack_type = parts[1]\n",
    "        attack_types.append(attack_type)\n",
    "        \n",
    "        # Load the pickle file into a dataframe\n",
    "        df = pd.DataFrame({'anomaly_score': pd.read_pickle(os.path.join(directory, filename))})\n",
    "        df['Attack Type'] = attack_type  # Add an 'Attack Type' column\n",
    "        df['Day'] = day  # Add a 'Day' column\n",
    "        dfs.append(df)\n",
    "\n",
    "# Assuming dfs is a list of DataFrames with columns: 'anomaly_score', 'Attack Type', and 'Day'\n",
    "\n",
    "# Combine all DataFrames into one\n",
    "combined_df = pd.concat(dfs, ignore_index=True)\n",
    "\n",
    "# Get unique days\n",
    "unique_days = combined_df['Day'].unique()\n",
    "\n",
    "def plot_boxplots(dfs, use_log_scale=False, include_outliers=True):\n",
    "    combined_df = pd.concat(dfs, ignore_index=True)\n",
    "    unique_days = combined_df['Day'].unique()\n",
    "    \n",
    "    days_order = ['UNSW', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']\n",
    "    combined_df['Day'] = pd.Categorical(combined_df['Day'], categories=days_order, ordered=True)\n",
    "    \n",
    "    for day in unique_days:\n",
    "        plt.figure(figsize=(8, 6))\n",
    "        day_data = combined_df[combined_df['Day'] == day]\n",
    "        save_data = day_data[['Attack Type', 'anomaly_score']]\n",
    "        with open(f'{day}_results.pickle', 'wb') as handle:\n",
    "            pickle.dump(save_data, handle)\n",
    "        title = f\"{day} - Boxplot of Reconstruction Error of Each Conversation by Attack Type\"\n",
    "        if use_log_scale and not include_outliers:\n",
    "            title += \" (Log Scale, Outliers Excluded)\"\n",
    "        elif use_log_scale:\n",
    "            title += \" (Log Scale)\"\n",
    "        elif not include_outliers:\n",
    "            title += \" (Outliers Excluded)\"\n",
    "\n",
    "        plt.title(title)\n",
    "        plt.xlabel(\"Attack Type\")\n",
    "        plt.ylabel(\"Reconstruction Error of Each Conversation\")\n",
    "\n",
    "        if use_log_scale:\n",
    "            plt.yscale('log')\n",
    "        day_data = day_data[~(day_data['Attack Type'].isin(['Web Attack - SQL Injection - New', 'Web Attack - SQL Injection - Attempted - New', 'Web Attack - XSS - New', 'Web Attack - XSS - Attempted - New']))]\n",
    "\n",
    "        sns.boxplot(x='Attack Type', y='anomaly_score', data=day_data, hue='Attack Type', showfliers=include_outliers, order=['Benign', 'Analysis', 'Backdoor', 'DoS', 'Exploits', 'Generic', 'Reconnaissance', 'Shellcode', 'Worms'])\n",
    "        \n",
    "        plt.xticks(rotation=45)\n",
    "        plt.xticks([], [])\n",
    "        line = plt.axhline(y=0.111996, label=\"MAD threshold: 0.073617\", color='orange')\n",
    "#         line = plt.axhline(y=0.0557, label=\"EER threshold: 0.0739\", linestyle='dashed')\n",
    "#        line = plt.axhline(y=0.032549, label=\"Test set reconstruction error threshold: 0.032549\", color='red', linestyle='dashed')\n",
    "        plt.legend(loc='upper center', bbox_to_anchor=(0.5, -0.15), shadow=True, ncol=2)\n",
    "        \n",
    "        plt.tight_layout()  # Ensures everything fits in the figure\n",
    "        \n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "413f3750",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[    anomaly_score              Attack Type     Day\n",
      "0        0.075300  benign - small - sanity  Friday\n",
      "1        0.006166  benign - small - sanity  Friday\n",
      "2        0.025531  benign - small - sanity  Friday\n",
      "3        0.005023  benign - small - sanity  Friday\n",
      "4        0.010906  benign - small - sanity  Friday\n",
      "..            ...                      ...     ...\n",
      "68       0.007306  benign - small - sanity  Friday\n",
      "69       0.005154  benign - small - sanity  Friday\n",
      "70       0.006747  benign - small - sanity  Friday\n",
      "71       0.004912  benign - small - sanity  Friday\n",
      "72       0.006885  benign - small - sanity  Friday\n",
      "\n",
      "[73 rows x 3 columns],     anomaly_score     Attack Type     Day\n",
      "0        0.047885  benign - small  Friday\n",
      "1        0.012147  benign - small  Friday\n",
      "2        0.016677  benign - small  Friday\n",
      "3        0.016743  benign - small  Friday\n",
      "4        0.018053  benign - small  Friday\n",
      "5        0.016159  benign - small  Friday\n",
      "6        0.014810  benign - small  Friday\n",
      "7        0.023639  benign - small  Friday\n",
      "8        0.010747  benign - small  Friday\n",
      "9        0.007310  benign - small  Friday\n",
      "10       0.009183  benign - small  Friday\n",
      "11       0.003496  benign - small  Friday\n",
      "12       0.009593  benign - small  Friday\n",
      "13       0.008622  benign - small  Friday\n",
      "14       0.004445  benign - small  Friday\n",
      "15       0.011729  benign - small  Friday\n",
      "16       0.012085  benign - small  Friday\n",
      "17       0.008946  benign - small  Friday\n",
      "18       0.009252  benign - small  Friday\n",
      "19       0.007265  benign - small  Friday\n",
      "20       0.026491  benign - small  Friday\n",
      "21       0.016929  benign - small  Friday\n",
      "22       0.009157  benign - small  Friday\n",
      "23       0.014372  benign - small  Friday\n",
      "24       0.004347  benign - small  Friday\n",
      "25       0.015464  benign - small  Friday\n",
      "26       0.014183  benign - small  Friday\n",
      "27       0.014317  benign - small  Friday\n",
      "28       0.014136  benign - small  Friday\n",
      "29       0.014602  benign - small  Friday\n",
      "30       0.015357  benign - small  Friday\n",
      "31       0.008496  benign - small  Friday\n",
      "32       0.013558  benign - small  Friday\n",
      "33       0.010859  benign - small  Friday\n",
      "34       0.008787  benign - small  Friday\n",
      "35       0.013701  benign - small  Friday\n",
      "36       0.005734  benign - small  Friday\n",
      "37       0.008303  benign - small  Friday\n",
      "38       0.007679  benign - small  Friday\n",
      "39       0.006875  benign - small  Friday\n",
      "40       0.011098  benign - small  Friday\n",
      "41       0.010167  benign - small  Friday\n",
      "42       0.006035  benign - small  Friday\n",
      "43       0.004808  benign - small  Friday\n",
      "44       0.048072  benign - small  Friday\n",
      "45       0.002895  benign - small  Friday\n",
      "46       0.005365  benign - small  Friday\n",
      "47       0.009668  benign - small  Friday,    anomaly_score         Attack Type     Day\n",
      "0       0.106251  Botnet - Attempted  Friday\n",
      "1       0.043489  Botnet - Attempted  Friday\n",
      "2       0.053639  Botnet - Attempted  Friday\n",
      "3       0.008827  Botnet - Attempted  Friday\n",
      "4       0.006455  Botnet - Attempted  Friday,     anomaly_score Attack Type     Day\n",
      "0        0.300669      Botnet  Friday\n",
      "1        0.064380      Botnet  Friday\n",
      "2        0.111652      Botnet  Friday\n",
      "3        0.026408      Botnet  Friday\n",
      "4        0.030309      Botnet  Friday\n",
      "..            ...         ...     ...\n",
      "74       0.087322      Botnet  Friday\n",
      "75       0.065253      Botnet  Friday\n",
      "76       0.050239      Botnet  Friday\n",
      "77       0.035462      Botnet  Friday\n",
      "78       0.094500      Botnet  Friday\n",
      "\n",
      "[79 rows x 3 columns],     anomaly_score Attack Type     Day\n",
      "0        0.119988        DDoS  Friday\n",
      "1        0.014968        DDoS  Friday\n",
      "2        0.016614        DDoS  Friday\n",
      "3        0.014774        DDoS  Friday\n",
      "4        0.012351        DDoS  Friday\n",
      "5        0.007771        DDoS  Friday\n",
      "6        0.030022        DDoS  Friday\n",
      "7        0.006207        DDoS  Friday\n",
      "8        0.007338        DDoS  Friday\n",
      "9        0.007126        DDoS  Friday\n",
      "10       0.004353        DDoS  Friday\n",
      "11       0.003511        DDoS  Friday\n",
      "12       0.052695        DDoS  Friday\n",
      "13       0.008521        DDoS  Friday\n",
      "14       0.009665        DDoS  Friday\n",
      "15       0.007618        DDoS  Friday\n",
      "16       0.017459        DDoS  Friday\n",
      "17       0.004747        DDoS  Friday\n",
      "18       0.004615        DDoS  Friday\n",
      "19       0.066958        DDoS  Friday\n",
      "20       0.033150        DDoS  Friday\n",
      "21       0.043436        DDoS  Friday\n",
      "22       0.058544        DDoS  Friday\n",
      "23       0.039389        DDoS  Friday\n",
      "24       0.024834        DDoS  Friday\n",
      "25       0.033062        DDoS  Friday\n",
      "26       0.042716        DDoS  Friday\n",
      "27       0.039729        DDoS  Friday\n",
      "28       0.037139        DDoS  Friday\n",
      "29       0.011292        DDoS  Friday\n",
      "30       0.006609        DDoS  Friday\n",
      "31       0.011414        DDoS  Friday\n",
      "32       0.007971        DDoS  Friday\n",
      "33       0.008879        DDoS  Friday\n",
      "34       0.003659        DDoS  Friday\n",
      "35       0.003659        DDoS  Friday\n",
      "36       0.036822        DDoS  Friday\n",
      "37       0.029906        DDoS  Friday\n",
      "38       0.026013        DDoS  Friday\n",
      "39       0.118655        DDoS  Friday\n",
      "40       0.116817        DDoS  Friday\n",
      "41       0.115808        DDoS  Friday\n",
      "42       0.119023        DDoS  Friday\n",
      "43       0.118279        DDoS  Friday\n",
      "44       0.118993        DDoS  Friday\n",
      "45       0.118449        DDoS  Friday\n",
      "46       0.115810        DDoS  Friday\n",
      "47       0.119202        DDoS  Friday\n",
      "48       0.119394        DDoS  Friday\n",
      "49       0.117742        DDoS  Friday\n",
      "50       0.116702        DDoS  Friday\n",
      "51       0.118946        DDoS  Friday\n",
      "52       0.116575        DDoS  Friday\n",
      "53       0.114432        DDoS  Friday\n",
      "54       0.117435        DDoS  Friday,     anomaly_score Attack Type     Day\n",
      "0        0.113751    Portscan  Friday\n",
      "1        0.105054    Portscan  Friday\n",
      "2        0.067371    Portscan  Friday\n",
      "3        0.066958    Portscan  Friday\n",
      "4        0.033150    Portscan  Friday\n",
      "5        0.043436    Portscan  Friday\n",
      "6        0.058544    Portscan  Friday\n",
      "7        0.039389    Portscan  Friday\n",
      "8        0.024834    Portscan  Friday\n",
      "9        0.033062    Portscan  Friday\n",
      "10       0.042716    Portscan  Friday\n",
      "11       0.039729    Portscan  Friday\n",
      "12       0.037139    Portscan  Friday\n",
      "13       0.015520    Portscan  Friday\n",
      "14       0.028384    Portscan  Friday\n",
      "15       0.036822    Portscan  Friday\n",
      "16       0.029906    Portscan  Friday\n",
      "17       0.026013    Portscan  Friday\n",
      "18       0.109962    Portscan  Friday\n",
      "19       0.106596    Portscan  Friday\n",
      "20       0.108895    Portscan  Friday\n",
      "21       0.108606    Portscan  Friday\n",
      "22       0.108455    Portscan  Friday\n",
      "23       0.109648    Portscan  Friday\n",
      "24       0.109722    Portscan  Friday\n",
      "25       0.108130    Portscan  Friday\n",
      "26       0.109690    Portscan  Friday\n",
      "27       0.108881    Portscan  Friday\n",
      "28       0.108050    Portscan  Friday\n",
      "29       0.108410    Portscan  Friday\n",
      "30       0.106210    Portscan  Friday\n",
      "31       0.108588    Portscan  Friday\n",
      "32       0.104984    Portscan  Friday,     anomaly_score              Attack Type       Day\n",
      "0        0.073083  benign - small - sanity  Thursday\n",
      "1        0.006448  benign - small - sanity  Thursday\n",
      "2        0.021628  benign - small - sanity  Thursday\n",
      "3        0.017382  benign - small - sanity  Thursday\n",
      "4        0.010193  benign - small - sanity  Thursday\n",
      "5        0.011862  benign - small - sanity  Thursday\n",
      "6        0.006339  benign - small - sanity  Thursday\n",
      "7        0.004334  benign - small - sanity  Thursday\n",
      "8        0.006560  benign - small - sanity  Thursday\n",
      "9        0.004567  benign - small - sanity  Thursday\n",
      "10       0.005424  benign - small - sanity  Thursday\n",
      "11       0.008122  benign - small - sanity  Thursday\n",
      "12       0.008000  benign - small - sanity  Thursday\n",
      "13       0.007857  benign - small - sanity  Thursday\n",
      "14       0.007258  benign - small - sanity  Thursday\n",
      "15       0.007614  benign - small - sanity  Thursday\n",
      "16       0.033597  benign - small - sanity  Thursday\n",
      "17       0.012472  benign - small - sanity  Thursday\n",
      "18       0.024211  benign - small - sanity  Thursday\n",
      "19       0.023737  benign - small - sanity  Thursday\n",
      "20       0.024005  benign - small - sanity  Thursday\n",
      "21       0.023676  benign - small - sanity  Thursday\n",
      "22       0.024190  benign - small - sanity  Thursday\n",
      "23       0.023080  benign - small - sanity  Thursday\n",
      "24       0.004132  benign - small - sanity  Thursday\n",
      "25       0.006790  benign - small - sanity  Thursday\n",
      "26       0.013115  benign - small - sanity  Thursday\n",
      "27       0.021888  benign - small - sanity  Thursday\n",
      "28       0.022819  benign - small - sanity  Thursday\n",
      "29       0.023440  benign - small - sanity  Thursday\n",
      "30       0.005202  benign - small - sanity  Thursday\n",
      "31       0.026124  benign - small - sanity  Thursday\n",
      "32       0.005632  benign - small - sanity  Thursday\n",
      "33       0.012650  benign - small - sanity  Thursday\n",
      "34       0.008591  benign - small - sanity  Thursday\n",
      "35       0.009550  benign - small - sanity  Thursday\n",
      "36       0.009742  benign - small - sanity  Thursday\n",
      "37       0.013834  benign - small - sanity  Thursday\n",
      "38       0.007020  benign - small - sanity  Thursday\n",
      "39       0.010688  benign - small - sanity  Thursday\n",
      "40       0.008357  benign - small - sanity  Thursday\n",
      "41       0.022306  benign - small - sanity  Thursday\n",
      "42       0.006909  benign - small - sanity  Thursday\n",
      "43       0.023010  benign - small - sanity  Thursday\n",
      "44       0.010286  benign - small - sanity  Thursday\n",
      "45       0.003544  benign - small - sanity  Thursday\n",
      "46       0.025040  benign - small - sanity  Thursday\n",
      "47       0.025793  benign - small - sanity  Thursday\n",
      "48       0.024518  benign - small - sanity  Thursday\n",
      "49       0.007007  benign - small - sanity  Thursday,     anomaly_score     Attack Type       Day\n",
      "0        0.085146  benign - small  Thursday\n",
      "1        0.084054  benign - small  Thursday\n",
      "2        0.018557  benign - small  Thursday\n",
      "3        0.025172  benign - small  Thursday\n",
      "4        0.016118  benign - small  Thursday\n",
      "..            ...             ...       ...\n",
      "59       0.007231  benign - small  Thursday\n",
      "60       0.006305  benign - small  Thursday\n",
      "61       0.008873  benign - small  Thursday\n",
      "62       0.005217  benign - small  Thursday\n",
      "63       0.029339  benign - small  Thursday\n",
      "\n",
      "[64 rows x 3 columns],     anomaly_score               Attack Type       Day\n",
      "0        0.047410  Infiltration - Attempted  Thursday\n",
      "1        0.019259  Infiltration - Attempted  Thursday\n",
      "2        0.013984  Infiltration - Attempted  Thursday\n",
      "3        0.010634  Infiltration - Attempted  Thursday\n",
      "4        0.005273  Infiltration - Attempted  Thursday\n",
      "5        0.014562  Infiltration - Attempted  Thursday\n",
      "6        0.008387  Infiltration - Attempted  Thursday\n",
      "7        0.005486  Infiltration - Attempted  Thursday\n",
      "8        0.005711  Infiltration - Attempted  Thursday\n",
      "9        0.016453  Infiltration - Attempted  Thursday\n",
      "10       0.017197  Infiltration - Attempted  Thursday\n",
      "11       0.005959  Infiltration - Attempted  Thursday\n",
      "12       0.008520  Infiltration - Attempted  Thursday\n",
      "13       0.006045  Infiltration - Attempted  Thursday\n",
      "14       0.017817  Infiltration - Attempted  Thursday\n",
      "15       0.007400  Infiltration - Attempted  Thursday\n",
      "16       0.015211  Infiltration - Attempted  Thursday\n",
      "17       0.015196  Infiltration - Attempted  Thursday\n",
      "18       0.006092  Infiltration - Attempted  Thursday\n",
      "19       0.015268  Infiltration - Attempted  Thursday\n",
      "20       0.015305  Infiltration - Attempted  Thursday\n",
      "21       0.005887  Infiltration - Attempted  Thursday\n",
      "22       0.006072  Infiltration - Attempted  Thursday\n",
      "23       0.006252  Infiltration - Attempted  Thursday\n",
      "24       0.006367  Infiltration - Attempted  Thursday\n",
      "25       0.006296  Infiltration - Attempted  Thursday\n",
      "26       0.006282  Infiltration - Attempted  Thursday\n",
      "27       0.006351  Infiltration - Attempted  Thursday\n",
      "28       0.006324  Infiltration - Attempted  Thursday,      anomaly_score   Attack Type       Day\n",
      "0         0.163610  Infiltration  Thursday\n",
      "1         0.020484  Infiltration  Thursday\n",
      "2         0.010552  Infiltration  Thursday\n",
      "3         0.013043  Infiltration  Thursday\n",
      "4         0.005898  Infiltration  Thursday\n",
      "..             ...           ...       ...\n",
      "331       0.007021  Infiltration  Thursday\n",
      "332       0.008796  Infiltration  Thursday\n",
      "333       0.009373  Infiltration  Thursday\n",
      "334       0.009300  Infiltration  Thursday\n",
      "335       0.009612  Infiltration  Thursday\n",
      "\n",
      "[336 rows x 3 columns],     anomaly_score                           Attack Type       Day\n",
      "0        0.139382  Web Attack - Brute Force - Attempted  Thursday\n",
      "1        0.013971  Web Attack - Brute Force - Attempted  Thursday\n",
      "2        0.022671  Web Attack - Brute Force - Attempted  Thursday\n",
      "3        0.083692  Web Attack - Brute Force - Attempted  Thursday\n",
      "4        0.031044  Web Attack - Brute Force - Attempted  Thursday\n",
      "..            ...                                   ...       ...\n",
      "65       0.007902  Web Attack - Brute Force - Attempted  Thursday\n",
      "66       0.005486  Web Attack - Brute Force - Attempted  Thursday\n",
      "67       0.005523  Web Attack - Brute Force - Attempted  Thursday\n",
      "68       0.005965  Web Attack - Brute Force - Attempted  Thursday\n",
      "69       0.004761  Web Attack - Brute Force - Attempted  Thursday\n",
      "\n",
      "[70 rows x 3 columns],     anomaly_score               Attack Type       Day\n",
      "0        0.139726  Web Attack - Brute Force  Thursday\n",
      "1        0.009709  Web Attack - Brute Force  Thursday\n",
      "2        0.020823  Web Attack - Brute Force  Thursday\n",
      "3        0.017259  Web Attack - Brute Force  Thursday\n",
      "4        0.008573  Web Attack - Brute Force  Thursday\n",
      "5        0.015210  Web Attack - Brute Force  Thursday\n",
      "6        0.008266  Web Attack - Brute Force  Thursday\n",
      "7        0.009122  Web Attack - Brute Force  Thursday\n",
      "8        0.009369  Web Attack - Brute Force  Thursday\n",
      "9        0.009660  Web Attack - Brute Force  Thursday\n",
      "10       0.025154  Web Attack - Brute Force  Thursday\n",
      "11       0.025255  Web Attack - Brute Force  Thursday\n",
      "12       0.022054  Web Attack - Brute Force  Thursday\n",
      "13       0.108723  Web Attack - Brute Force  Thursday\n",
      "14       0.108634  Web Attack - Brute Force  Thursday\n",
      "15       0.183390  Web Attack - Brute Force  Thursday\n",
      "16       0.106753  Web Attack - Brute Force  Thursday\n",
      "17       0.126790  Web Attack - Brute Force  Thursday\n",
      "18       0.106314  Web Attack - Brute Force  Thursday\n",
      "19       0.106369  Web Attack - Brute Force  Thursday\n",
      "20       0.104660  Web Attack - Brute Force  Thursday\n",
      "21       0.107218  Web Attack - Brute Force  Thursday\n",
      "22       0.008362  Web Attack - Brute Force  Thursday\n",
      "23       0.044337  Web Attack - Brute Force  Thursday\n",
      "24       0.104172  Web Attack - Brute Force  Thursday\n",
      "25       0.103533  Web Attack - Brute Force  Thursday\n",
      "26       0.104762  Web Attack - Brute Force  Thursday\n",
      "27       0.017013  Web Attack - Brute Force  Thursday\n",
      "28       0.008885  Web Attack - Brute Force  Thursday\n",
      "29       0.024887  Web Attack - Brute Force  Thursday\n",
      "30       0.105222  Web Attack - Brute Force  Thursday\n",
      "31       0.102505  Web Attack - Brute Force  Thursday\n",
      "32       0.104216  Web Attack - Brute Force  Thursday\n",
      "33       0.104876  Web Attack - Brute Force  Thursday\n",
      "34       0.092178  Web Attack - Brute Force  Thursday\n",
      "35       0.005141  Web Attack - Brute Force  Thursday\n",
      "36       0.005162  Web Attack - Brute Force  Thursday\n",
      "37       0.086220  Web Attack - Brute Force  Thursday\n",
      "38       0.091196  Web Attack - Brute Force  Thursday\n",
      "39       0.092116  Web Attack - Brute Force  Thursday\n",
      "40       0.089414  Web Attack - Brute Force  Thursday\n",
      "41       0.062785  Web Attack - Brute Force  Thursday\n",
      "42       0.073686  Web Attack - Brute Force  Thursday\n",
      "43       0.091622  Web Attack - Brute Force  Thursday\n",
      "44       0.104824  Web Attack - Brute Force  Thursday\n",
      "45       0.010701  Web Attack - Brute Force  Thursday\n",
      "46       0.085911  Web Attack - Brute Force  Thursday\n",
      "47       0.092238  Web Attack - Brute Force  Thursday\n",
      "48       0.059074  Web Attack - Brute Force  Thursday\n",
      "49       0.021089  Web Attack - Brute Force  Thursday\n",
      "50       0.020677  Web Attack - Brute Force  Thursday\n",
      "51       0.015347  Web Attack - Brute Force  Thursday\n",
      "52       0.007807  Web Attack - Brute Force  Thursday,     anomaly_score                             Attack Type       Day\n",
      "0        0.030807  Web Attack - SQL Injection - Attempted  Thursday\n",
      "1        0.008651  Web Attack - SQL Injection - Attempted  Thursday\n",
      "2        0.010093  Web Attack - SQL Injection - Attempted  Thursday\n",
      "3        0.006305  Web Attack - SQL Injection - Attempted  Thursday\n",
      "4        0.006338  Web Attack - SQL Injection - Attempted  Thursday\n",
      "5        0.006041  Web Attack - SQL Injection - Attempted  Thursday\n",
      "6        0.006641  Web Attack - SQL Injection - Attempted  Thursday\n",
      "7        0.008528  Web Attack - SQL Injection - Attempted  Thursday\n",
      "8        0.006325  Web Attack - SQL Injection - Attempted  Thursday\n",
      "9        0.008218  Web Attack - SQL Injection - Attempted  Thursday\n",
      "10       0.008228  Web Attack - SQL Injection - Attempted  Thursday\n",
      "11       0.006472  Web Attack - SQL Injection - Attempted  Thursday\n",
      "12       0.005493  Web Attack - SQL Injection - Attempted  Thursday\n",
      "13       0.008317  Web Attack - SQL Injection - Attempted  Thursday\n",
      "14       0.008363  Web Attack - SQL Injection - Attempted  Thursday\n",
      "15       0.010743  Web Attack - SQL Injection - Attempted  Thursday\n",
      "16       0.006138  Web Attack - SQL Injection - Attempted  Thursday\n",
      "17       0.009344  Web Attack - SQL Injection - Attempted  Thursday\n",
      "18       0.009436  Web Attack - SQL Injection - Attempted  Thursday,     anomaly_score                 Attack Type       Day\n",
      "0        0.047030  Web Attack - SQL Injection  Thursday\n",
      "1        0.008465  Web Attack - SQL Injection  Thursday\n",
      "2        0.016697  Web Attack - SQL Injection  Thursday\n",
      "3        0.008221  Web Attack - SQL Injection  Thursday\n",
      "4        0.006395  Web Attack - SQL Injection  Thursday\n",
      "5        0.008668  Web Attack - SQL Injection  Thursday\n",
      "6        0.008259  Web Attack - SQL Injection  Thursday\n",
      "7        0.008683  Web Attack - SQL Injection  Thursday\n",
      "8        0.008262  Web Attack - SQL Injection  Thursday\n",
      "9        0.008586  Web Attack - SQL Injection  Thursday\n",
      "10       0.008259  Web Attack - SQL Injection  Thursday\n",
      "11       0.015641  Web Attack - SQL Injection  Thursday\n",
      "12       0.008274  Web Attack - SQL Injection  Thursday\n",
      "13       0.008685  Web Attack - SQL Injection  Thursday\n",
      "14       0.008246  Web Attack - SQL Injection  Thursday\n",
      "15       0.008257  Web Attack - SQL Injection  Thursday\n",
      "16       0.008412  Web Attack - SQL Injection  Thursday\n",
      "17       0.008483  Web Attack - SQL Injection  Thursday,     anomaly_score                   Attack Type       Day\n",
      "0        0.106105  Web Attack - XSS - Attempted  Thursday\n",
      "1        0.006214  Web Attack - XSS - Attempted  Thursday\n",
      "2        0.013978  Web Attack - XSS - Attempted  Thursday\n",
      "3        0.022255  Web Attack - XSS - Attempted  Thursday\n",
      "4        0.018440  Web Attack - XSS - Attempted  Thursday\n",
      "5        0.009587  Web Attack - XSS - Attempted  Thursday\n",
      "6        0.011402  Web Attack - XSS - Attempted  Thursday\n",
      "7        0.006973  Web Attack - XSS - Attempted  Thursday\n",
      "8        0.007645  Web Attack - XSS - Attempted  Thursday\n",
      "9        0.009237  Web Attack - XSS - Attempted  Thursday\n",
      "10       0.007675  Web Attack - XSS - Attempted  Thursday\n",
      "11       0.009700  Web Attack - XSS - Attempted  Thursday\n",
      "12       0.011085  Web Attack - XSS - Attempted  Thursday\n",
      "13       0.009425  Web Attack - XSS - Attempted  Thursday\n",
      "14       0.037291  Web Attack - XSS - Attempted  Thursday\n",
      "15       0.015254  Web Attack - XSS - Attempted  Thursday\n",
      "16       0.035172  Web Attack - XSS - Attempted  Thursday\n",
      "17       0.029940  Web Attack - XSS - Attempted  Thursday\n",
      "18       0.008237  Web Attack - XSS - Attempted  Thursday\n",
      "19       0.018461  Web Attack - XSS - Attempted  Thursday\n",
      "20       0.007581  Web Attack - XSS - Attempted  Thursday\n",
      "21       0.009465  Web Attack - XSS - Attempted  Thursday\n",
      "22       0.006685  Web Attack - XSS - Attempted  Thursday\n",
      "23       0.012831  Web Attack - XSS - Attempted  Thursday\n",
      "24       0.014376  Web Attack - XSS - Attempted  Thursday\n",
      "25       0.013898  Web Attack - XSS - Attempted  Thursday\n",
      "26       0.011530  Web Attack - XSS - Attempted  Thursday\n",
      "27       0.008302  Web Attack - XSS - Attempted  Thursday\n",
      "28       0.008028  Web Attack - XSS - Attempted  Thursday,     anomaly_score       Attack Type       Day\n",
      "0        0.101216  Web Attack - XSS  Thursday\n",
      "1        0.009997  Web Attack - XSS  Thursday\n",
      "2        0.012614  Web Attack - XSS  Thursday\n",
      "3        0.007992  Web Attack - XSS  Thursday\n",
      "4        0.007896  Web Attack - XSS  Thursday\n",
      "5        0.007558  Web Attack - XSS  Thursday\n",
      "6        0.007761  Web Attack - XSS  Thursday\n",
      "7        0.007519  Web Attack - XSS  Thursday\n",
      "8        0.015943  Web Attack - XSS  Thursday\n",
      "9        0.026268  Web Attack - XSS  Thursday\n",
      "10       0.007943  Web Attack - XSS  Thursday\n",
      "11       0.014302  Web Attack - XSS  Thursday\n",
      "12       0.004929  Web Attack - XSS  Thursday\n",
      "13       0.014921  Web Attack - XSS  Thursday\n",
      "14       0.010188  Web Attack - XSS  Thursday\n",
      "15       0.114984  Web Attack - XSS  Thursday\n",
      "16       0.008942  Web Attack - XSS  Thursday\n",
      "17       0.011705  Web Attack - XSS  Thursday\n",
      "18       0.005538  Web Attack - XSS  Thursday\n",
      "19       0.037156  Web Attack - XSS  Thursday\n",
      "20       0.026842  Web Attack - XSS  Thursday\n",
      "21       0.032046  Web Attack - XSS  Thursday\n",
      "22       0.022818  Web Attack - XSS  Thursday\n",
      "23       0.024512  Web Attack - XSS  Thursday\n",
      "24       0.021186  Web Attack - XSS  Thursday\n",
      "25       0.015100  Web Attack - XSS  Thursday\n",
      "26       0.016630  Web Attack - XSS  Thursday\n",
      "27       0.018177  Web Attack - XSS  Thursday\n",
      "28       0.008670  Web Attack - XSS  Thursday\n",
      "29       0.007788  Web Attack - XSS  Thursday\n",
      "30       0.011929  Web Attack - XSS  Thursday\n",
      "31       0.024679  Web Attack - XSS  Thursday\n",
      "32       0.017595  Web Attack - XSS  Thursday\n",
      "33       0.009015  Web Attack - XSS  Thursday\n",
      "34       0.007044  Web Attack - XSS  Thursday\n",
      "35       0.009034  Web Attack - XSS  Thursday\n",
      "36       0.014806  Web Attack - XSS  Thursday\n",
      "37       0.008217  Web Attack - XSS  Thursday\n",
      "38       0.008706  Web Attack - XSS  Thursday\n",
      "39       0.008629  Web Attack - XSS  Thursday\n",
      "40       0.005197  Web Attack - XSS  Thursday,     anomaly_score              Attack Type      Day\n",
      "0        0.094666  benign - small - sanity  Tuesday\n",
      "1        0.006293  benign - small - sanity  Tuesday\n",
      "2        0.013303  benign - small - sanity  Tuesday\n",
      "3        0.009691  benign - small - sanity  Tuesday\n",
      "4        0.006872  benign - small - sanity  Tuesday\n",
      "..            ...                      ...      ...\n",
      "58       0.013411  benign - small - sanity  Tuesday\n",
      "59       0.023254  benign - small - sanity  Tuesday\n",
      "60       0.007662  benign - small - sanity  Tuesday\n",
      "61       0.007830  benign - small - sanity  Tuesday\n",
      "62       0.004230  benign - small - sanity  Tuesday\n",
      "\n",
      "[63 rows x 3 columns],      anomaly_score     Attack Type      Day\n",
      "0         0.094760  benign - small  Tuesday\n",
      "1         0.082806  benign - small  Tuesday\n",
      "2         0.030785  benign - small  Tuesday\n",
      "3         0.064190  benign - small  Tuesday\n",
      "4         0.056569  benign - small  Tuesday\n",
      "..             ...             ...      ...\n",
      "96        0.023631  benign - small  Tuesday\n",
      "97        0.023834  benign - small  Tuesday\n",
      "98        0.023877  benign - small  Tuesday\n",
      "99        0.023962  benign - small  Tuesday\n",
      "100       0.012110  benign - small  Tuesday\n",
      "\n",
      "[101 rows x 3 columns],     anomaly_score              Attack Type      Day\n",
      "0        0.095505  FTP-Patator - Attempted  Tuesday\n",
      "1        0.020657  FTP-Patator - Attempted  Tuesday\n",
      "2        0.095510  FTP-Patator - Attempted  Tuesday\n",
      "3        0.016762  FTP-Patator - Attempted  Tuesday\n",
      "4        0.013673  FTP-Patator - Attempted  Tuesday\n",
      "5        0.011922  FTP-Patator - Attempted  Tuesday\n",
      "6        0.006552  FTP-Patator - Attempted  Tuesday\n",
      "7        0.010354  FTP-Patator - Attempted  Tuesday\n",
      "8        0.012229  FTP-Patator - Attempted  Tuesday\n",
      "9        0.017427  FTP-Patator - Attempted  Tuesday\n",
      "10       0.026387  FTP-Patator - Attempted  Tuesday,     anomaly_score  Attack Type      Day\n",
      "0        0.156447  FTP-Patator  Tuesday\n",
      "1        0.113310  FTP-Patator  Tuesday\n",
      "2        0.099760  FTP-Patator  Tuesday\n",
      "3        0.113298  FTP-Patator  Tuesday\n",
      "4        0.090970  FTP-Patator  Tuesday\n",
      "5        0.093010  FTP-Patator  Tuesday\n",
      "6        0.087471  FTP-Patator  Tuesday\n",
      "7        0.099829  FTP-Patator  Tuesday\n",
      "8        0.094761  FTP-Patator  Tuesday\n",
      "9        0.092181  FTP-Patator  Tuesday\n",
      "10       0.093534  FTP-Patator  Tuesday\n",
      "11       0.094722  FTP-Patator  Tuesday\n",
      "12       0.090985  FTP-Patator  Tuesday\n",
      "13       0.096324  FTP-Patator  Tuesday\n",
      "14       0.064943  FTP-Patator  Tuesday\n",
      "15       0.090727  FTP-Patator  Tuesday\n",
      "16       0.091025  FTP-Patator  Tuesday\n",
      "17       0.100282  FTP-Patator  Tuesday\n",
      "18       0.068372  FTP-Patator  Tuesday\n",
      "19       0.091868  FTP-Patator  Tuesday\n",
      "20       0.046165  FTP-Patator  Tuesday\n",
      "21       0.080948  FTP-Patator  Tuesday\n",
      "22       0.088869  FTP-Patator  Tuesday\n",
      "23       0.089809  FTP-Patator  Tuesday\n",
      "24       0.074229  FTP-Patator  Tuesday\n",
      "25       0.037656  FTP-Patator  Tuesday\n",
      "26       0.005222  FTP-Patator  Tuesday\n",
      "27       0.069968  FTP-Patator  Tuesday\n",
      "28       0.058282  FTP-Patator  Tuesday\n",
      "29       0.038228  FTP-Patator  Tuesday\n",
      "30       0.004852  FTP-Patator  Tuesday\n",
      "31       0.004863  FTP-Patator  Tuesday\n",
      "32       0.004880  FTP-Patator  Tuesday,     anomaly_score              Attack Type      Day\n",
      "0        0.090275  SSH-Patator - Attempted  Tuesday\n",
      "1        0.042062  SSH-Patator - Attempted  Tuesday\n",
      "2        0.011352  SSH-Patator - Attempted  Tuesday\n",
      "3        0.010036  SSH-Patator - Attempted  Tuesday\n",
      "4        0.010011  SSH-Patator - Attempted  Tuesday\n",
      "5        0.009941  SSH-Patator - Attempted  Tuesday\n",
      "6        0.009563  SSH-Patator - Attempted  Tuesday\n",
      "7        0.010450  SSH-Patator - Attempted  Tuesday\n",
      "8        0.009829  SSH-Patator - Attempted  Tuesday\n",
      "9        0.009776  SSH-Patator - Attempted  Tuesday\n",
      "10       0.012792  SSH-Patator - Attempted  Tuesday\n",
      "11       0.021663  SSH-Patator - Attempted  Tuesday,     anomaly_score  Attack Type      Day\n",
      "0        0.131734  SSH-Patator  Tuesday\n",
      "1        0.093832  SSH-Patator  Tuesday\n",
      "2        0.100231  SSH-Patator  Tuesday\n",
      "3        0.103628  SSH-Patator  Tuesday\n",
      "4        0.092198  SSH-Patator  Tuesday\n",
      "5        0.097146  SSH-Patator  Tuesday\n",
      "6        0.093427  SSH-Patator  Tuesday\n",
      "7        0.098310  SSH-Patator  Tuesday\n",
      "8        0.109628  SSH-Patator  Tuesday\n",
      "9        0.117752  SSH-Patator  Tuesday\n",
      "10       0.108913  SSH-Patator  Tuesday\n",
      "11       0.104862  SSH-Patator  Tuesday\n",
      "12       0.092804  SSH-Patator  Tuesday\n",
      "13       0.004466  SSH-Patator  Tuesday\n",
      "14       0.004344  SSH-Patator  Tuesday\n",
      "15       0.007853  SSH-Patator  Tuesday\n",
      "16       0.022644  SSH-Patator  Tuesday\n",
      "17       0.016917  SSH-Patator  Tuesday\n",
      "18       0.013726  SSH-Patator  Tuesday\n",
      "19       0.019363  SSH-Patator  Tuesday\n",
      "20       0.022278  SSH-Patator  Tuesday\n",
      "21       0.017813  SSH-Patator  Tuesday\n",
      "22       0.019998  SSH-Patator  Tuesday\n",
      "23       0.023310  SSH-Patator  Tuesday\n",
      "24       0.014110  SSH-Patator  Tuesday\n",
      "25       0.004347  SSH-Patator  Tuesday\n",
      "26       0.004674  SSH-Patator  Tuesday\n",
      "27       0.019234  SSH-Patator  Tuesday\n",
      "28       0.014032  SSH-Patator  Tuesday\n",
      "29       0.014109  SSH-Patator  Tuesday\n",
      "30       0.012972  SSH-Patator  Tuesday,     anomaly_score              Attack Type        Day\n",
      "0        0.109851  benign - small - sanity  Wednesday\n",
      "1        0.010798  benign - small - sanity  Wednesday\n",
      "2        0.012550  benign - small - sanity  Wednesday\n",
      "3        0.012599  benign - small - sanity  Wednesday\n",
      "4        0.012027  benign - small - sanity  Wednesday\n",
      "..            ...                      ...        ...\n",
      "84       0.011876  benign - small - sanity  Wednesday\n",
      "85       0.004311  benign - small - sanity  Wednesday\n",
      "86       0.011985  benign - small - sanity  Wednesday\n",
      "87       0.013023  benign - small - sanity  Wednesday\n",
      "88       0.018409  benign - small - sanity  Wednesday\n",
      "\n",
      "[89 rows x 3 columns],      anomaly_score     Attack Type        Day\n",
      "0         0.051829  benign - small  Wednesday\n",
      "1         0.024478  benign - small  Wednesday\n",
      "2         0.009574  benign - small  Wednesday\n",
      "3         0.026688  benign - small  Wednesday\n",
      "4         0.006013  benign - small  Wednesday\n",
      "..             ...             ...        ...\n",
      "217       0.019452  benign - small  Wednesday\n",
      "218       0.019767  benign - small  Wednesday\n",
      "219       0.019942  benign - small  Wednesday\n",
      "220       0.019832  benign - small  Wednesday\n",
      "221       0.019993  benign - small  Wednesday\n",
      "\n",
      "[222 rows x 3 columns],      anomaly_score                Attack Type        Day\n",
      "0         0.129542  DoS GoldenEye - Attempted  Wednesday\n",
      "1         0.101908  DoS GoldenEye - Attempted  Wednesday\n",
      "2         0.011979  DoS GoldenEye - Attempted  Wednesday\n",
      "3         0.017065  DoS GoldenEye - Attempted  Wednesday\n",
      "4         0.121825  DoS GoldenEye - Attempted  Wednesday\n",
      "..             ...                        ...        ...\n",
      "145       0.123452  DoS GoldenEye - Attempted  Wednesday\n",
      "146       0.123718  DoS GoldenEye - Attempted  Wednesday\n",
      "147       0.123557  DoS GoldenEye - Attempted  Wednesday\n",
      "148       0.116097  DoS GoldenEye - Attempted  Wednesday\n",
      "149       0.127973  DoS GoldenEye - Attempted  Wednesday\n",
      "\n",
      "[150 rows x 3 columns],      anomaly_score    Attack Type        Day\n",
      "0         0.176452  DoS GoldenEye  Wednesday\n",
      "1         0.083193  DoS GoldenEye  Wednesday\n",
      "2         0.036029  DoS GoldenEye  Wednesday\n",
      "3         0.071726  DoS GoldenEye  Wednesday\n",
      "4         0.093836  DoS GoldenEye  Wednesday\n",
      "..             ...            ...        ...\n",
      "552       0.065024  DoS GoldenEye  Wednesday\n",
      "553       0.083473  DoS GoldenEye  Wednesday\n",
      "554       0.083924  DoS GoldenEye  Wednesday\n",
      "555       0.081087  DoS GoldenEye  Wednesday\n",
      "556       0.081122  DoS GoldenEye  Wednesday\n",
      "\n",
      "[557 rows x 3 columns],      anomaly_score           Attack Type        Day\n",
      "0         0.132554  DoS Hulk - Attempted  Wednesday\n",
      "1         0.101908  DoS Hulk - Attempted  Wednesday\n",
      "2         0.050542  DoS Hulk - Attempted  Wednesday\n",
      "3         0.020198  DoS Hulk - Attempted  Wednesday\n",
      "4         0.022989  DoS Hulk - Attempted  Wednesday\n",
      "..             ...                   ...        ...\n",
      "190       0.071316  DoS Hulk - Attempted  Wednesday\n",
      "191       0.092666  DoS Hulk - Attempted  Wednesday\n",
      "192       0.100409  DoS Hulk - Attempted  Wednesday\n",
      "193       0.062484  DoS Hulk - Attempted  Wednesday\n",
      "194       0.068725  DoS Hulk - Attempted  Wednesday\n",
      "\n",
      "[195 rows x 3 columns],      anomaly_score Attack Type        Day\n",
      "0         2.335194    DoS Hulk  Wednesday\n",
      "1         0.153430    DoS Hulk  Wednesday\n",
      "2         0.093836    DoS Hulk  Wednesday\n",
      "3         0.036238    DoS Hulk  Wednesday\n",
      "4         0.071726    DoS Hulk  Wednesday\n",
      "..             ...         ...        ...\n",
      "553       0.065024    DoS Hulk  Wednesday\n",
      "554       0.083473    DoS Hulk  Wednesday\n",
      "555       0.083924    DoS Hulk  Wednesday\n",
      "556       0.081087    DoS Hulk  Wednesday\n",
      "557       0.081122    DoS Hulk  Wednesday\n",
      "\n",
      "[558 rows x 3 columns],      anomaly_score                   Attack Type        Day\n",
      "0         2.335194  DoS Slowhttptest - Attempted  Wednesday\n",
      "1         0.132933  DoS Slowhttptest - Attempted  Wednesday\n",
      "2         0.016798  DoS Slowhttptest - Attempted  Wednesday\n",
      "3         0.133194  DoS Slowhttptest - Attempted  Wednesday\n",
      "4         0.092245  DoS Slowhttptest - Attempted  Wednesday\n",
      "..             ...                           ...        ...\n",
      "481       0.063613  DoS Slowhttptest - Attempted  Wednesday\n",
      "482       0.066646  DoS Slowhttptest - Attempted  Wednesday\n",
      "483       0.071576  DoS Slowhttptest - Attempted  Wednesday\n",
      "484       0.074277  DoS Slowhttptest - Attempted  Wednesday\n",
      "485       0.055148  DoS Slowhttptest - Attempted  Wednesday\n",
      "\n",
      "[486 rows x 3 columns],      anomaly_score       Attack Type        Day\n",
      "0         1.000485  DoS Slowhttptest  Wednesday\n",
      "1         0.067324  DoS Slowhttptest  Wednesday\n",
      "2         1.565223  DoS Slowhttptest  Wednesday\n",
      "3         0.133056  DoS Slowhttptest  Wednesday\n",
      "4         0.012964  DoS Slowhttptest  Wednesday\n",
      "..             ...               ...        ...\n",
      "423       0.060720  DoS Slowhttptest  Wednesday\n",
      "424       0.076713  DoS Slowhttptest  Wednesday\n",
      "425       0.060501  DoS Slowhttptest  Wednesday\n",
      "426       0.059469  DoS Slowhttptest  Wednesday\n",
      "427       0.059298  DoS Slowhttptest  Wednesday\n",
      "\n",
      "[428 rows x 3 columns],      anomaly_score                Attack Type        Day\n",
      "0         0.130331  DoS Slowloris - Attempted  Wednesday\n",
      "1         0.047021  DoS Slowloris - Attempted  Wednesday\n",
      "2         0.060028  DoS Slowloris - Attempted  Wednesday\n",
      "3         0.129527  DoS Slowloris - Attempted  Wednesday\n",
      "4         0.013766  DoS Slowloris - Attempted  Wednesday\n",
      "..             ...                        ...        ...\n",
      "330       0.061787  DoS Slowloris - Attempted  Wednesday\n",
      "331       0.064223  DoS Slowloris - Attempted  Wednesday\n",
      "332       0.061699  DoS Slowloris - Attempted  Wednesday\n",
      "333       0.060652  DoS Slowloris - Attempted  Wednesday\n",
      "334       0.081716  DoS Slowloris - Attempted  Wednesday\n",
      "\n",
      "[335 rows x 3 columns],      anomaly_score    Attack Type        Day\n",
      "0         0.144253  DoS Slowloris  Wednesday\n",
      "1         0.153430  DoS Slowloris  Wednesday\n",
      "2         0.036238  DoS Slowloris  Wednesday\n",
      "3         0.047563  DoS Slowloris  Wednesday\n",
      "4         0.128561  DoS Slowloris  Wednesday\n",
      "..             ...            ...        ...\n",
      "348       0.060830  DoS Slowloris  Wednesday\n",
      "349       0.062513  DoS Slowloris  Wednesday\n",
      "350       0.083051  DoS Slowloris  Wednesday\n",
      "351       0.061448  DoS Slowloris  Wednesday\n",
      "352       0.082306  DoS Slowloris  Wednesday\n",
      "\n",
      "[353 rows x 3 columns],     anomaly_score Attack Type        Day\n",
      "0        0.107525  Heartbleed  Wednesday\n",
      "1        0.014533  Heartbleed  Wednesday\n",
      "2        0.005022  Heartbleed  Wednesday\n",
      "3        0.003783  Heartbleed  Wednesday\n",
      "4        0.017633  Heartbleed  Wednesday\n",
      "5        0.098076  Heartbleed  Wednesday\n",
      "6        0.104673  Heartbleed  Wednesday\n",
      "7        0.106536  Heartbleed  Wednesday\n",
      "8        0.113526  Heartbleed  Wednesday\n",
      "9        0.109073  Heartbleed  Wednesday\n",
      "10       0.105354  Heartbleed  Wednesday\n",
      "11       0.105659  Heartbleed  Wednesday\n",
      "12       0.104391  Heartbleed  Wednesday\n",
      "13       0.104880  Heartbleed  Wednesday\n",
      "14       0.103621  Heartbleed  Wednesday\n",
      "15       0.103869  Heartbleed  Wednesday\n",
      "16       0.093137  Heartbleed  Wednesday\n",
      "17       0.104562  Heartbleed  Wednesday\n",
      "18       0.102269  Heartbleed  Wednesday\n",
      "19       0.102458  Heartbleed  Wednesday\n",
      "20       0.104602  Heartbleed  Wednesday\n",
      "21       0.102615  Heartbleed  Wednesday\n",
      "22       0.100407  Heartbleed  Wednesday\n",
      "23       0.102938  Heartbleed  Wednesday\n",
      "24       0.105639  Heartbleed  Wednesday\n",
      "25       0.099226  Heartbleed  Wednesday\n",
      "26       0.097681  Heartbleed  Wednesday\n",
      "27       0.098852  Heartbleed  Wednesday\n",
      "28       0.099610  Heartbleed  Wednesday\n",
      "29       0.098468  Heartbleed  Wednesday\n",
      "30       0.098085  Heartbleed  Wednesday\n",
      "31       0.095779  Heartbleed  Wednesday\n",
      "32       0.097291  Heartbleed  Wednesday\n",
      "33       0.096186  Heartbleed  Wednesday\n",
      "34       0.097065  Heartbleed  Wednesday\n",
      "35       0.046814  Heartbleed  Wednesday\n",
      "36       0.045408  Heartbleed  Wednesday]\n"
     ]
    }
   ],
   "source": [
    "print(dfs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "bed3ca47",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['benign - small' 'Botnet - Attempted' 'Botnet' 'DDoS' 'Portscan']\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['benign - small' 'Infiltration - Attempted' 'Infiltration'\n",
      " 'Web Attack - Brute Force - Attempted' 'Web Attack - Brute Force'\n",
      " 'Web Attack - SQL Injection - Attempted' 'Web Attack - SQL Injection'\n",
      " 'Web Attack - XSS - Attempted' 'Web Attack - XSS']\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['benign - small' 'FTP-Patator - Attempted' 'FTP-Patator'\n",
      " 'SSH-Patator - Attempted' 'SSH-Patator']\n"
     ]
    },
    {
     "data": {
      "image/png": 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gYGCK7X716lVTtGhR07Fjx3SXY4wxly5dMn5+frbf7xkzZhhJJiIiwjbOqVOnbL8/U6ZMsW2nU6dO3fKY1qtXLzNz5kyzZs0as2bNGjNq1Cjj5eVlwsPD7eK41bEz+fOoVKmS7f2ECROMq6urGTVq1C3X80YhISGmTZs2tveTJ082FovF9juaLPm4kXy8yOjnYkzG9/O0lCpVyjz22GMpylM7v7xZRs4VjDHmo48+MpJM+/btzYoVK0xkZKQpV66cCQkJMSEhIeku48KFCyZfvnwmMDDQfPTRR3a/gzc7d+6cqVSpksmTJ48ZOXKkiYqKMp9//rl5/vnnzbp162zjZXRfufl7mZiYaFq2bGny5MljwsPDzZo1a8yMGTNMUFCQCQ0NNZcuXbKbfuvWrUaSWb58ebrreCMSFpNyw48ePdq4uLikOIH87LPPjCSzatUqY4wx48aNM5LsTthu9vLLLxuLxWJ27dplV/7ggw+mSFhulJSUZK5evWqOHDliJJlly5bZhiX/iOzcudNWtm3bNiPJzJkzJ81YsiIkJMRISvGqW7euOX78uG28xMREU7RoUVOlShWTmJhoKz9//rwpVKiQadCgga0sPj7e1KhRw5QsWdLExMSYwoULm0aNGtmdlCWfJBctWtRcvnzZVn7u3Dnj7+9vHnjggRTbI/nL+u+//xovL68UP16xsbHG09PTdOnSxVY2YMCAVE+EU5OZ+aaVhKTm5hPV8+fPm9WrV5vAwEBz//33252gVahQwdSoUSPFSdtDDz1kihQpYtv2vXv3Nu7u7iYmJibN5b7yyitGktm6datd+TPPPGMsFovZv3+/Meb/P4sqVarYfUbJ+9yCBQuMMcacPn3aSDKTJk1Kd30rVapk931LlvxDdP/996cYltGE5Y8//jCurq6pnrTdqE2bNmn+GNycsDz++OPG09PTxMbG2o3XqlUr4+3tbfv+J8d/8/6xePFiW1KcnuR1Se3l6uqaIkY/Pz/zzz//pDqPHj162JXv27fPSDL9+/e3K0/+0XjttddsZY0aNTKSzNq1a9ON15jMfe+Tt8+SJUtuOd/kcdN6/fnnn6lOl3zc3Lhxo5Fkdu/ebRtWunRpU7p0abvjyc2S97OxY8falffv399YrVbbxarULFy40Egy06dPv+X6GWPM9OnTjSSzePFiu/IxY8YYSeabb76xlUkyhQsXNufOnbOVnThxwri4uJjRo0fbyoYMGWK8vLzsfpNiYmKMJPPBBx/YyjJ6HElrfzLGGB8fHzNo0KAMrasx6f+mvffeeykuPCS7+fc5J7ZbapL3wZo1a9p97ocPHzbu7u6mT58+trLhw4cbDw8Pc/LkSVvZokWLjKR0k/1kn376qd2+c/78eePj42Puu+8+u/GWLFmS5nlDese0GyUmJpqrV6+akSNHmgIFCtjWLaPHzuSEJTEx0QwcONB4eHiYefPm3XK5N7s5YTl37pzx9fU1zz//vN14oaGhdhcfMvO5ZHQ/T83JkyeNJPPuu++mGHarhCWj5wqJiYkmMDDQ1KtXz268I0eOGHd39wx9nitXrjQFCxa0HRsLFChgOnbsmCIRGDlypJFk1qxZc8t5JktrXzEm5fdywYIFKS6wGmNMdHS0kWSmTp1qV37lyhVjsVgyfIHHGGNyVZOwjFqxYoUqV66s6tWr69q1a7ZXixYt7Kqq69SpI0l67LHHtHjxYv31118p5rV+/XpVqlRJ1apVsyvv0qVLinFPnTqlfv36KTg4WG5ubnJ3d1dISIgk2VUjdu7cWYUKFbI1Z5Ku90gVEBCgTp06pbtuN67PtWvXMlTNd++99yo6OlrR0dHavHmzZs6cqb///ltNmza1Ve3v379fx44dU/fu3e2qIX18fNS+fXv9+OOPtuptT09PLV68WHFxcapZs6aMMVqwYIFcXV1TLPvRRx+V1Wq1vff19VXbtm21adMmJSYmphrvDz/8oMuXL6dohhUcHKymTZtmuEnZnZpvsnvuuUfu7u7y9fVVy5YtlT9/fi1btsx2/8bvv/+uX3/9VV27dpVk/1m2bt1ax48ftzU9+vrrr9WkSRNVrFgxzeWtW7dOoaGhKe6x6dWrl4wxKTqsaNOmjd1nVLVqVUnSkSNHJEn+/v4qXbq03nvvPU2YMEE7d+7MUhva9u3bZ3qaZGvWrFFiYqKt+UB2WLdunZo1a6bg4GC78l69eunSpUspmoI8/PDDdu9v3k638umnn9q+b8mvrVu3phivadOmaXbGcPM2XL9+vS3mG9WtW1cVK1ZMse/mz59fTZs2vWWsmfneZ8WYMWNSbIvo6GgVLlzYNs4ff/yhLl26KDAwUK6urnJ3d7fdI5N83Dxw4IAOHjyoJ5980u54kpbUPsP4+HidOnUqy+tys3Xr1ilPnjzq0KGDXXnyZ3TzZ9KkSRO7jjsKFy6sQoUK2e1XvXv31uXLl7Vo0SJb2ezZs+Xp6Wn7zcnMcSRZat/JunXrKiIiQm+99ZZ+/PHHVHs/y+hvWmbkxHZLT5cuXeyaV4WEhKhBgwa275QkPfPMM5KuN+1J9uGHH6pKlSq6//77b7mMmTNnysvLS48//rik69+fjh076rvvvsuWniLXrVunBx54QH5+frbvyJtvvqm4uDjbPp2ZY2d8fLweeeQRRUZG6ptvvrHtS7fD19dXTzzxhCIiImzNOdetW6eYmBgNHDgwxfi3+lyysp/fKLkZX6FChTK9Lhk9V9i/f79OnDihxx57zG684sWLq2HDhhlaVuvWrRUbG6svv/xSL7zwgipVqqSlS5fq4YcftttuX3/9tcqVK6cHHngg3fllZF9JzYoVK5QvXz61bdvWbltXr15dgYGBKXq5dHd3V758+VI9b04LCUsqTp48qT179sjd3d3u5evrK2OM7ST9/vvv19KlS3Xt2jX16NFDxYoVU+XKle3uL4mLi1NgYGCKZdxclpSUpObNm+uLL77QSy+9pLVr12rbtm22ewQuX75sG9fT01NPP/205s+frzNnzujvv//W4sWL1adPH3l6eqa7bjev083t8FPj5+en2rVrq3bt2mrQoIF69+6t+fPna9++fRo/frxtPaXU21IWLVpUSUlJ+vfff21lZcqU0X333af4+Hh17do1zTaYaW27K1eu6MKFC6lOc6tYkodnVk7NN1nyieq6dev09NNPa9++fercubNtePK9Jy+88EKKz7F///6SZNs3//7771v2dBUXF5fmuiQPv1GBAgXs3ifva8n7ZnL7+RYtWmjs2LGqWbOmAgIC9Nxzz2WqnWpa+0JGJLeVzc5evrJ7O91KxYoVbd+35FetWrVSjJfedrp5WGb33Yx+Bpn93mdWqVKlUmyL2rVr2+6du3Dhgu677z5t3bpVb731ljZs2KDo6Gh98cUXkv5/m2d2v8jKZ1i8eHFJ12+EzYjk34ab780qVKiQ3NzcbrlfJcd1Y0yVKlVSnTp1NHv2bElSYmKi5s2bp7CwMPn7+0vK3HEkWWqf76JFi9SzZ0/NmDFD9evXl7+/v3r06KETJ05IytxvWmbkxHZLT1q/QTcup3DhwurUqZM++ugjJSYmas+ePfruu+9SPdG+2e+//65NmzapTZs2MsbozJkzOnPmjC0hS+45LKu2bdum5s2bS7qeUG3evFnR0dF6/fXXJWXtO3Lq1ClFRUWpfv36atCgwW3Fd6Nnn31W58+fV2RkpKTrSV+xYsUUFhaWYtxbfS5Z2c9vlLxdMnKB42YZPd4m/73xAkyy1MrS4uXlpUceeUTvvfeeNm7cqN9//12hoaGaMmWKrQOgjJwTZHRfSc3Jkyd15swZeXh4pNjeJ06cSHVbW63WTB0H7ppewjLCarWmuClPur7TFixY0Pa+YMGC8vLySvNAceO4YWFhCgsLU0JCgn788UeNHj1aXbp0UYkSJVS/fn0VKFDAdgC/0c1le/fu1e7duxUREaGePXvaytPqUeaZZ57Ru+++q1mzZik+Pl7Xrl1Tv3790t8AUoob8kuWLHnLaVKTfNV49+7dkv7/R+H48eMpxj127JhcXFzsrgbPmDFDK1euVN26dfXhhx+qU6dOqfaIkta28/DwSLMf9FvFcuPnlxk5Nd9kySeq0vWrgomJiZoxY4Y+++wzdejQwTb/V199VY8++miq80juIjAgICDFzdQ3K1CgQJrrIilL6xMSEmK7QfPAgQNavHixRowYoStXrmj69OkZmkdqN9cn/2gkJCTYJeU3HwQDAgIkSUePHk1RI5JVObGdskN6vTTdPOzGfffmH63U9t2M9gCV2e99dlu3bp2OHTumDRs22PU8dvPzPG7cL3JK7dq15e/vr2XLlmn06NG33IYFChTQ1q1bZYyxG/fUqVO6du1alverJ554Qv3799e+ffv0xx9/6Pjx43a9DGbmOJIstXUpWLCgJk2apEmTJik2NlbLly/XK6+8olOnTmn16tWZ/k3LqJzabmlJ6zfo5kTo+eef19y5c7Vs2TKtXr1a+fLly1DNw6xZs2SM0WeffZbqM1/mzJmjt956K9UWCBmxcOFCubu7a8WKFXYn30uXLrUbLzPHzuLFi2vChAlq166dHn30US1ZsiRLJ/Y3K1OmjFq1aqUpU6aoVatWWr58ucLDw1Nd91t9LlnZz2+UPP0///yT6fXI6LlC8ng3d6wjpb5+GVW8eHE99dRTGjRokH755RdVqlQpQ+cEGd1XUlOwYEEVKFAgzR7VUnusw7///pup72uuqmEpUaKEXS8p0vWTqpurBR966CEdPHhQBQoUSPXqXmo9N3h6eqpRo0YaM2aMJNl6q2jSpIl++eUX24l9svnz59u9Tz7w3lxD8tFHH6W6LkWKFFHHjh01depUTZ8+XW3btrVd4UvPzeuS2tWnjEju9Sm5urR8+fIKCgrS/Pnz7ZqZXbx4UZ9//rmtByFJ+vnnn/Xcc8+pR48e+u6771S1alV16tQp1SuxX3zxheLj423vz58/r6+++kr33Xdfmgfw+vXry8vLS/PmzbMrP3r0qK15T7LMXP3OzHyzw9ixY5U/f369+eabSkpKUvny5VW2bFnt3r071f2ydu3atoNCq1attH79+nSrvJs1a6aYmBj99NNPduXJvc2l9vyLzChXrpzeeOMNValSxW4Zmbm6mSz5O3fz9/err76ye9+8eXO5urpq2rRp6c4vMzE0a9bMdmJ8o08//VTe3t5O3S1nsuTmXTfvu9HR0dq3b1+W993MfO9zQkaPm+XKlVPp0qU1a9asVC9aZQd3d3e9/PLL+vXXXzVq1KhUxzl16pQ2b94s6fp+deHChRQnA59++qlteFZ07txZVqtVERERioiIUFBQkO2qqaRMHUcyqnjx4ho4cKAefPBB23c9M79pmTkO59R2S8uCBQvs9u0jR45oy5YtKXouq1Wrlho0aKAxY8YoMjJSvXr1Up48edKdd2JioubMmaPSpUtr/fr1KV5Dhw7V8ePH9fXXX0tKfzuldUxL7hb+xt/Ly5cva+7cuXbjZfTYeeP4UVFR2rRpkx566KFUe+XLiueff1579uxRz5495erqqr59+6Y63q0+l9vdz0NCQuTl5aWDBw9meh0yeq5Qvnx5BQYGpui1LDY2Vlu2bLnlcs6fP59mS5PkJpfJLQFatWqlAwcOpGjqfaOM7iupeeihhxQXF6fExMRUt/XNyeGxY8cUHx+fqW7Lc1UNS/fu3dWtWzf1799f7du315EjRzR27FjblYVkgwYN0ueff677779fgwcPVtWqVZWUlKTY2Fh98803Gjp0qOrVq6c333xTR48eVbNmzVSsWDGdOXNGkydPtmtDPWjQIM2aNUtt2rTRW2+9pcKFCysyMtKuGzlJqlChgkqXLq1XXnlFxhj5+/vrq6++snXzm5rnn3/eViuR3AQgJ5w5c8ZWjX/16lXt27dP77zzjjw9PW3tXV1cXDR27Fh17dpVDz30kJ5++mklJCTovffe05kzZ/Tuu+9Kun4i89hjj6lkyZKaOnWqPDw8tHjxYtWsWVNPPPFEih8hV1dXPfjggxoyZIiSkpI0ZswYnTt3zq7P8Zvly5dPw4YN02uvvaYePXqoc+fOiouLU3h4uKxWq4YPH24bt0qVKpKut5Vv1aqVXF1dVbVqVXl4eNzWfLND/vz59eqrr+qll17S/Pnz1a1bN3300Udq1aqVWrRooV69eikoKEj//POP9u3bp59++klLliyRdL07za+//lr333+/XnvtNVWpUkVnzpzR6tWrNWTIEFWoUEGDBw/Wp59+qjZt2mjkyJEKCQnRypUrNXXqVD3zzDOZfr7Onj17NHDgQHXs2FFly5aVh4eH1q1bpz179uiVV16xjVelShUtXLhQixYtUqlSpWS1Wm2fQ1pat24tf39/Pfnkkxo5cqTc3NwUERGhP//80268EiVK6LXXXtOoUaN0+fJlW9e0MTExOn36tG2/qVKlir744gtNmzZNtWrVkouLS5rPPhk+fLhWrFihJk2a6M0335S/v78iIyO1cuVKjR071tbFd3bZu3dvql2Dli5dOsWxKqPKly+vp556Sh988IFcXFzUqlUrHT58WMOGDVNwcLAGDx6cpflm9HufVb/99luKrrOl681WihUrpgYNGih//vzq16+fhg8fLnd3d0VGRqa4QCRJU6ZMUdu2bXXPPfdo8ODBKl68uGJjYxUVFWVrgnK7XnzxRe3bt0/Dhw/Xtm3b1KVLF9uDIzdt2qSPP/5Y4eHhatiwoXr06KEpU6aoZ8+eOnz4sKpUqaLvv/9e77zzjlq3bn3LtuZpyZcvn9q1a6eIiAidOXNGL7zwQoruTTN6HEnL2bNn1aRJE3Xp0kUVKlSQr6+voqOjtXr1atvV7Mz8piV//ydPnqyePXvK3d1d5cuXT/WEMqe2W1pOnTqldu3aqW/fvjp79qyGDx8uq9WqV199NcW4zz//vK3b7uRmR+n5+uuvdezYMY0ZMybVbr4rV66sDz/8UDNnztRDDz1ke8L8xx9/LF9fX1mtVpUsWVIFChRI85jWpk0bTZgwQV26dNFTTz2luLg4jRs3LkUimdFj543uvfderV27Vi1btlTz5s21atWq2z4ePvjggwoNDdX69ettXe6nJiOfy+3s5x4eHql23Z8sMTEx1RqxPHnyqFWrVhk6V3BxcVF4eLiefvppdejQQb1799aZM2cUHh6uIkWKpPje3mz//v1q0aKFHn/8cTVq1EhFihTRv//+q5UrV+rjjz9W48aNbU32Bg0apEWLFiksLEyvvPKK6tatq8uXL2vjxo166KGH1KRJkwzvK6l5/PHHFRkZqdatW+v5559X3bp15e7urqNHj2r9+vUKCwuze4hl8nbN1IXRDN+e/x+TWi8OSUlJZuzYsaZUqVLGarWa2rVrm3Xr1qXo7cCY693FvfHGG6Z8+fLGw8PD+Pn5mSpVqpjBgwebEydOGGOMWbFihWnVqpUJCgoyHh4eplChQqZ169Z2Xfgac72XlgcffNBYrVbj7+9vnnzySbNs2bIUvX0kj+fr62vy589vOnbsaGJjY1P0WnSjEiVKmIoVK9729krLzb2Eubq6muLFi5sOHTrY9VKWbOnSpaZevXrGarWaPHnymGbNmpnNmzfbhnfr1s14e3un6NI0ufeTiRMnGmP+v2eqMWPGmPDwcFOsWDHj4eFhatSoYaKiouymTa1rW2Oudw1ZtWpV2+cXFhaWYrkJCQmmT58+JiAgwFgsljR7qsnsfLPSS1hq416+fDlFt7i7d+82jz32mClUqJBxd3c3gYGBpmnTpil6J/rzzz9N7969TWBgoHF3dzdFixY1jz32mF1PNkeOHDFdunQxBQoUMO7u7qZ8+fLmvffes+s9JfmzeO+991LEd+O+efLkSdOrVy9ToUIFkydPHuPj42OqVq1qJk6caNe72OHDh03z5s2Nr6+vkWTrCeVWvUht27bNNGjQwOTJk8cEBQWZ4cOH27r/vPkz+/TTT02dOnWM1Wo1Pj4+pkaNGnbdWP7zzz+mQ4cOJl++fLbPPbV1Svbzzz+btm3bGj8/P+Ph4WGqVauWolvMtOJP3n636kYzvV7CJJlPPvnELsYBAwakOY/U9qXExEQzZswYU65cOePu7m4KFixounXrlqLHrZu7Lc2IW33vjcneXsJef/1127hbtmwx9evXN97e3iYgIMD06dPH/PTTT6lu8x9++MG0atXK+Pn5GU9PT1O6dGkzePBg2/DkXsJu7ObZmLSPMWlZtmyZadOmjQkICDBubm4mf/78pkmTJmb69OkmISHBNl5cXJzp16+fKVKkiHFzczMhISHm1VdfTdG1elqfd1o9X37zzTe2bXVzN7HJMnIcSWt/io+PN/369TNVq1Y1efPmNV5eXqZ8+fJm+PDh5uLFi7bxMvOb9uqrr5qiRYsaFxcXu9/G1H6fc2q73Sh5H5w7d6557rnnTEBAgPH09DT33Xef2b59e6rTJCQkGE9PT9OyZct0553skUceMR4eHubUqVNpjvP4448bNzc323nHpEmTTMmSJY2rq6vdPp7eMW3WrFmmfPnyxtPT05QqVcqMHj3azJw5M0vHztSOD3v37jWBgYGmZs2aKb47abm5l7AbjRgxwuh/PWfeLLOfS0Z/L1Mzc+ZM4+rqao4dO2ZX3rNnzzSPTTf27JWRcwVjjPn4449NmTJljIeHhylXrpyZNWuWCQsLMzVq1Eg3vn///de89dZbpmnTprbz0Dx58pjq1aubt956K0VXwv/++695/vnnTfHixY27u7spVKiQadOmjfn1119t42R0X0nte3n16lUzbtw4U61aNdv+U6FCBfP000+b3377zW7c7t27mypVqqS7fjezGJOBbqLglPbs2aNq1appypQpGbqa819y+PBhlSxZUu+9955eeOEFR4cDAEC6vvrqKz388MNauXKlWrdu7ehw/rNq166d5kOwN2zYoCZNmmjJkiUpeorLbvHx8SpevLiGDh2ql19+OUeXdaMzZ86oXLlyeuSRRzL1JPj/inPnzqlo0aKaOHFimk3+UpOrmoTdLQ4ePKgjR47otddeU5EiRbL0FHUAAHD7YmJidOTIEQ0dOlTVq1dXq1atHB3Sf865c+e0d+9erVixQjt27NCXX37p6JBktVoVHh6uESNGaODAgbe8JykrTpw4obfffltNmjRRgQIFdOTIEU2cOFHnz5/X888/n+3LcwYTJ05U8eLF7ToDyQgSlv+gUaNGae7cuapYsaKWLFmSoze1AgCAtPXv31+bN29WzZo1NWfOnAz3sof/99NPP9lO2ocPH65HHnnE0SFJkp566imdOXNGf/zxxy3vtcwKT09PHT58WP3799c///xj68hl+vTpqlSpUrYvzxnkzZtXERERtmfMZRRNwgAAAAA4rVzVrTEAAACA/xYSFgAAAABOi4QFAAAAgNPipvtbSEpK0rFjx+Tr68uNdAAAAMhVjDE6f/68ihYtessHWuYUEpZbOHbsmIKDgx0dBgAAAOAwf/75p4oVK+aQZZOw3IKvr6+k6x9S3rx5HRwNAAAAcOecO3dOwcHBtnNiRyBhuYXkZmB58+YlYQEAAECu5MhbI7jpHgAAAIDTImEBAAAA4LRIWAAAAAA4LRIWAAAAAE6LhAUAAACA0yJhAQAAAOC0SFgAAAAAOC0SFgAAAABOi4QFAAAAgNMiYQEAAADgtEhYAABOa/PmzerYsaM2b97s6FAAAA5CwgIAcErx8fEaP368Tp48qfHjxys+Pt7RIQEAHICEBQDglObNm6e4uDhJUlxcnCIjIx0cEQDAEUhYAABO5+jRo4qMjJQxRpJkjFFkZKSOHj3q4MgAAHcaCQsAwKkYYzRx4sQ0y5OTGABA7kDCAgBwKkeOHFF0dLQSExPtyhMTExUdHa0jR444KDIAgCOQsAAAnEpISIjq1KkjV1dXu3JXV1fVrVtXISEhDooMAOAIJCwAAKdisVg0ePDgNMstFosDogIAOAoJCwDA6RQrVkxdu3a1JScWi0Vdu3ZVUFCQgyMDANxpJCwAAKfUrVs3FShQQJJUsGBBde3a1cERAQAcgYQFAOCUrFarhg4dqsKFC2vIkCGyWq2ODgkA4AAWQ/+Q6Tp37pz8/Px09uxZ5c2b19HhAAAAAHeMM5wLU8MCAAAAwGmRsAAAAABwWiQsAAAAAJwWCQsAAAAAp0XCAgAAAMBpkbAAAAAAcFokLAAAAACcFgkLAAAAAKfl5ugAAAAAAKTOGKP4+PhUyxMSEiRJnp6eslgsdsOtVmuKsv8qEhYAAADAScXHx6tFixaZni4qKkpeXl45ENGdR5MwAAAAAE6LGhYAAADASVmtVkVFRaUoj4+PV1hYmCRp2bJlslqtKaa7W5CwAAAAAE7KYrHcsmmX1Wq9a5p/pYYmYQAAAACcFgkLAAAAAKdFwgIAAADAaZGwAAAAAHBaJCwAAAAAnBYJCwAAAACnRcICAAAAwGmRsAAAAABwWiQsAAAAAJwWCQsAAAAAp+Xm6AAAADDGKD4+PkVZQkKCJMnT01MWiyXFdFarNdVyAMDdg4Qlo65dlK65OjoKALgrxV++rLCwsExPt2zZMnl5eeVARADg5K5dltUt8X//X5SuJeXQci7mzHwzwWKMMY4OwpmdO3dOfn5+OvuJlNfb0dEAAAAAd865S5JfX+ns2bPKmzevQ2LgHhYAAAAATosmYRn16DHJQVklAORGl29oJkbTLwCwd8eOkefOSX2L5sy8M4iEJaPc8lx/AQDuDDcXxSffO+iWR3IjYQEAmzt1jEy+T8aBaBIGAAAAwGmRsAAAAABwWrkiYWnXrp3y58+vDh06ODoUAAAAAJmQKxKW5557Tp9++qmjwwAAAACQSbkiYWnSpIl8fX0dHQYAAACATHJ4wrJp0ya1bdtWRYsWlcVi0dKlS1OMM3XqVJUsWVJWq1W1atXSd999d+cDBQAAAHDHOTxhuXjxoqpVq6YPP/ww1eGLFi3SoEGD9Prrr2vnzp2677771KpVK8XGxtrGqVWrlipXrpzidezYsTu1GgAAAABygMOfw9KqVSu1atUqzeETJkzQk08+qT59+kiSJk2apKioKE2bNk2jR4+WJO3YsSPb4klISFBCQoLt/blz57Jt3sB/wYwZMzRv3jx169bN9r0DAABwFIfXsKTnypUr2rFjh5o3b25X3rx5c23ZsiVHljl69Gj5+fnZXsHBwTmynBtt3rxZHTt21ObNm3N8WUB6zpw5o3nz5ikpKUnz5s3TmTNnHB0SAAC5gjFGly9fzvArPj7eNm18fHyGpzPGOHAts8bhNSzpOX36tBITE1W4cGG78sKFC+vEiRMZnk+LFi30008/6eLFiypWrJi+/PJL1alTJ9VxX331VQ0ZMsT2/ty5czmatMTHx2v8+PE6ffq0xo8fr1q1aslqtebY8oD0vP7660pKSpIkJSUl6Y033kizuSYAAMg+8fHxatGiRZamDQsLy/C4UVFR8vLyytJyHMWpE5ZkFovF7r0xJkVZeqKiojI8rqenpzw9PTM8/u2aN2+e4uLiJElxcXGKjIzUk08+eceWDyTbvn27fv75Z7uyPXv2aPv27apdu7aDogIAALmdUycsBQsWlKura4ralFOnTqWodfkvOnr0qCIjI21Vc8YYRUZGqkWLFipWrJiDo0NukpSUpBEjRqQ6bMSIEVq+fLlcXJy6BSn+I4wxds0Y0nNzc4eMslqtmbqoBQDO5uHq/eXm4p7uOMYYJSZdkyS5urile9y7lnRVy3dNzdYY7ySnTlg8PDxUq1YtrVmzRu3atbOVr1mzJlNVX87IGKOJEyemWT5u3Dh+cHHH/PDDD2l2MHHu3Dn98MMPatiw4R2OCnejrDZ5uNubOwDAjdxc3OXm6nHL8dx151oFOZLDL5leuHBBu3bt0q5duyRJhw4d0q5du2zdFg8ZMkQzZszQrFmztG/fPg0ePFixsbHq16+fA6O+fUeOHFF0dLQSExPtyhMTExUdHa0jR444KDLkRvXr11fevHlTHebn56f69evf4YgAwPnQSQ7gGA6vYdm+fbuaNGlie598w3vPnj0VERGhTp06KS4uTiNHjtTx48dVuXJlrVq1SiEhIY4KOVuEhISoTp062r59u11vDRaLRXXq1PnPrx/+W1xcXDRixAi7DieShYeH0xwMOSKxbWL6v0JGUvI1HVdJ6VU6X5Ncv3LNttiAm9FJDuA4Dj8Lady4sYwxKV4RERG2cfr376/Dhw8rISFBO3bs0P333++4gLOJxWJR586dU3QtZ4xR586daQ6GO6527dqqUqWKXVnVqlVVs2ZNB0WEu1GmutO06HpC46b0k5XbWQaQQal1kgPgznB4DUtuZYzRggULUh02f/581axZk6QFd9zbb7+tRx55RElJSXJxcdFbb73l6JBwl7nxwbw5VSOSkJAgb2/vHJk3cic6yQEcy+E1LLlV8j0sqeEeFjhKvnz51K1bN7m4uKhbt27Kly+fo0MCAIe6VSc51OgBOY8aljRMmTJFU6ZMSXFTfHYpXry48ubNm2rPTHnz5lXx4sVzZLnArfTp00d9+vRxdBi4S934nKtb3sOSGTfcw3Inn6WFu19aFxhv7CSnRIkSdz4wIBehhiUNAwYMUExMTJq1ILcrNjY23W5kk3tJA4C7iV1TV7dsfqW2DOA2JXeS4+pq34TR1dVVdevWpZMc4A4gYXGQ5BqW1FDDAgCAc7BYLBo8eHCa5STIQM4jYXEQalgAAPhvKFasmLp27WpLTiwWi7p27aqgoCAHRwbkDiQsDpJcxXzzlRmLxUIVMwAATqZbt24qUKCAJKlgwYLq2rWrgyMCcg8SFgdJq4pZElXMAAA4GavVqqFDh6pw4cIaMmQID40E7iB6CXNCdJEIAIDzadiwoRo2bOjoMIBchxoWB0nuvz21JmH06w4AAABcR8LiIMn9uiclJdmVJyUl8eBIAAAA4H9IWByEft0BAACAWyNhcZDkm+5Ta/rFTfcAAADAdSQsDlSsWDFVqlTJrqxSpUr06w4AAAD8DwlLGqZMmaLQ0FDVqVMnx5Zx9OhRxcTE2JXFxMTo6NGjObZMAAAA4L+EhCUNAwYMUExMjKKjo3Nk/sm9hN3cJCwpKYlewgAAAID/IWFxEHoJAwAAAG6NhMVBQkJCVKVKlVSHVa1alV7CAAAAAJGwOBQ9gQEAAADpI2FxkCNHjmjPnj2pDtuzZw9NwgAAAACRsDhM8oMjXVzsPwIeHAkAAAD8PxIWB0l+cOTNzcLSKgcAAAByIxIWBypWrJi6du1qS04sFou6du3KgyMBAACA/yFhcbBu3bqpQIECkqSCBQuqa9euDo4IAAAAcB4kLA5mtVo1dOhQFS5cWEOGDJHVanV0SAAAAIDTcHN0AJAaNmyohg0bOjoMAAAAwOlQwwIAAADAaZGwpGHKlCkKDQ1VnTp1HB0KAAAAkGuRsKRhwIABiomJUXR0tKNDAQAAAHItEhYnsHnzZnXs2FGbN292dCgAAACAUyFhcbD4+HiNGjVKJ0+e1KhRoxQfH+/okAAAAACnQcLiYDNmzNClS5ckSZcuXdLMmTMdHBEAAADgPEhYHOjo0aNavHixXdmiRYt09OhRB0UEAHfQtVu8rkqK/9/ragbGBwDclXgOi4MYYxQeHp7qsPDwcH388ceyWCx3OCoAuHNcv3J1dAgAgP8Aalgc5PDhw9q/f3+qw/bv36/Dhw/f2YAAAAAAJ0QNi4P89ddftxxesmTJOxQNANwZVqtVUVFRGRo3Pj5eYWFhkqRly5bJarVmeBkAgLsHCYuDNGjQQN7e3rYb7m/k7e2tBg0aOCAqAMhZFotFXl5emZ7OarVmaToAwH8fTcIcxGKxKDg4ONVhwcHB3L8CAAAAiITFYY4cOZLuPSxHjhy5wxEBAAAAzoeExUFCQkJUp06dFDUpLi4uqlu3rkJCQhwUGQAAAOA8SFgcxGKxaPDgwXJxsf8IXFxcNHjwYJqEAQAAACJhcahixYqpa9eutuTEYrGoa9euCgoKcnBkAAAAgHMgYUnDlClTFBoaqjp16uTocrp16yZfX19JUt68edW1a9ccXR4AAADwX0LCkoYBAwYoJiZG0dHROb4sY4wkKSkpKceXBQAAAPyXkLA42Lx583T+/HlJ0vnz5xUZGengiAAAAADnQcLiQEePHtW8efPsyubNm6ejR486KCIAAADAuZCwOIgxRhMnTrQ1B0uWlJSUajkAAACQG5GwOMiRI0cUHR2dIjExxig6OpoHRwIAAAAiYXGY4sWLK2/evKkOy5s3r4oXL36HIwIAAACcDwmLg8TGxurcuXOpDjt37pxiY2PvcEQAAACA8yFhcZCQkBDVqVMnxRPtLRaL6tatq5CQEAdFBgAAADgPEhYHsVgsGjx4sFxc7D8CV1dXDR48OEUiAwAAAORGJCwOVKxYMXXt2tWWnFgsFnXt2lVBQUEOjgwAAABwDiQsDtatWzcVKFBAklSwYEF17drVwREBAAAAzoOExcGsVquGDh2qwoULa8iQIbJarY4OCQAAAHAabo4OAFLDhg3VsGFDR4cBAAAAOB1qWAAAAAA4LRIWAAAAAE6LhAUAAACA0yJhScOUKVMUGhqqOnXqODoUAAAAINciYUnDgAEDFBMTo+joaEeHAgAAAORaJCwAAAAAnBYJCwAAAACnRcICAAAAwGmRsAAAAABwWiQsAAAAAJwWCQsAAAAAp0XCAgAAAMBpkbAAAAAAcFokLAAAAACcFgkLAAAAAKdFwgIAAJABmzdvVseOHbV582ZHhwLkKiQsAAAAtxAfH6/x48fr5MmTGj9+vOLj4x0dEpBrkLAAAADcwrx58xQXFydJiouLU2RkpIMjAnIPEhYAAIB0HD16VJGRkTLGSJKMMYqMjNTRo0cdHBmQO5CwAAAApMEYo4kTJ6ZZnpzEAMg5JCwAAABpOHLkiKKjo5WYmGhXnpiYqOjoaB05csRBkQG5BwkLAABAGkJCQlSnTh25urralbu6uqpu3boKCQlxUGRA7kHCAgAAkAaLxaLBgwenWW6xWBwQFZC7kLAAAACko1ixYuratastObFYLOratauCgoIcHBmQO5CwAAAA3EK3bt1UoEABSVLBggXVtWtXB0cE5B4kLGmYMmWKQkNDVadOHUeHAgAAHMxqtWro0KEqXLiwhgwZIqvV6uiQgFzDzdEBOKsBAwZowIABOnfunPz8/BwdDgAAcLCGDRuqYcOGjg4DyHWoYQEAAADgtLKcsBw8eFBvvPGGOnfurFOnTkmSVq9erV9++SXbggMAAACQu2UpYdm4caOqVKmirVu36osvvtCFCxckSXv27NHw4cOzNUAAwN3PGKPLly/bveLj423D4+PjUwy/fPkyTxkHgFwgS/ewvPLKK3rrrbc0ZMgQ+fr62sqbNGmiyZMnZ1twAIDcIT4+Xi1atEhzeFhYWKrlUVFR8vLyyqmwAABOIEsJy88//6z58+enKA8ICFBcXNxtB3W3MsbYXTFMLktISJAkeXp6pvoAKqvVyoOpAAAAkCtlKWHJly+fjh8/rpIlS9qV79y5k4copeNWVxDTwhVEAHc7q9WqqKgou7KMXtABANzdspSwdOnSRS+//LKWLFkii8WipKQkbd68WS+88IJ69OiR3TECAO5yFosl1Qsz3t7eDogGAOBMspSwvP322+rVq5eCgoJkjFFoaKgSExPVpUsXvfHGG9kd410jtSuI8fHxtrbZy5YtS/VqIVcQAQAAkFtlOmExxujYsWP65JNPNGrUKP30009KSkpSjRo1VLZs2ZyI8a6R1hXEZFarlaZfAAAAwA2ylLCULVtWv/zyi8qWLatSpUrlRFwAAAAAkPnnsLi4uKhs2bL0BgYAAAAgx2XpwZFjx47Viy++qL1792Z3PAAAAABgk6Wb7rt166ZLly6pWrVq8vDwSHHfxT///JMtwQEAAADI3bKUsEyaNCmbwwAAAACAlLKUsPTs2TO74wAAAACAFLKUsEhSYmKili5dqn379slisSg0NFQPP/ywXF1dszM+AAAAALlYlhKW33//Xa1bt9Zff/2l8uXLyxijAwcOKDg4WCtXrlTp0qWzO04AAAAAuVCWegl77rnnVLp0af3555/66aeftHPnTsXGxqpkyZJ67rnnsjtGAAAAALlUlmpYNm7cqB9//FH+/v62sgIFCujdd99Vw4YNsy04AAAAALlblmpYPD09df78+RTlFy5ckIeHx20HBQAAAABSFhOWhx56SE899ZS2bt0qY4yMMfrxxx/Vr18/Pfzww9kdIwAAAIBcKksJy/vvv6/SpUurfv36slqtslqtatiwocqUKaPJkydnd4wAAAAAcqks3cOSL18+LVu2TL///rv27dsnY4xCQ0NVpkyZ7I4PAAAAQC6W5eewSFKZMmVIUgAAAADkmCw1CevQoYPefffdFOXvvfeeOnbseNtBAQAAAICUxYRl48aNatOmTYryli1batOmTbcdFAAAAABIWUxY0uq+2N3dXefOnbvtoJzBlClTFBoaqjp16jg6FAAAACDXylLCUrlyZS1atChF+cKFCxUaGnrbQTmDAQMGKCYmRtHR0Y4OBQAAAMi1snTT/bBhw9S+fXsdPHhQTZs2lSStXbtWCxYs0JIlS7I1QAAAAAC5V5YSlocfflhLly7VO++8o88++0xeXl6qWrWqvv32WzVq1Ci7YwQAAACQS2W5W+M2bdqkeuM9AAAAAGSXLN3D8ueff+ro0aO299u2bdOgQYP08ccfZ1tgAAAAAJClhKVLly5av369JOnEiRN64IEHtG3bNr322msaOXJktgYIAAAAIPfKUsKyd+9e1a1bV5K0ePFiValSRVu2bNH8+fMVERGRnfEBAAAAyMWylLBcvXpVnp6ekqRvv/1WDz/8sCSpQoUKOn78ePZFBwAAACBXy1LCUqlSJU2fPl3fffed1qxZo5YtW0qSjh07pgIFCmRrgAAAAAByrywlLGPGjNFHH32kxo0bq3PnzqpWrZokafny5bamYgAAAABwu7LUrXHjxo11+vRpnTt3Tvnz57eVP/XUU/L29ra937x5s2rXrm1rPgbAeRhjFB8fn6IsISFBkuTp6SmLxZJiOqvVmmo5AABATsjyc1hcXV3tkhVJKlGihN37Vq1aadeuXSpVqlRWFwMgh8THx6tFixaZni4qKkpeXl45EBEAAEBKWWoSllHGmJycPQAAAIC7XJZrWAD8t1mtVkVFRdmVxcfHKywsTJK0bNkyWa3WVKcDAAC4U0hYckBq9wak5cbxMjqNxH0EuH0WiyXdpl1Wq5WmXwAAwOFIWHJAVu8NSL6ynRHcRwAAAIDcIEfvYaEGAAAAAMDtyNEaFm66ly7W7Cq5pLOZjZGSrl3/38VNSi/JS7qmPD9FZm+AAAAAgBPLUg3LiBEjdOTIkVuOd/78ebo0dnGTXN3Tfrl5SB7e119uHumPm17iAwAAANyFspSwfPXVVypdurSaNWum+fPnZ+pmcQAAAADIqCwlLDt27NBPP/2kqlWravDgwSpSpIieeeYZRUdHZ3d8AAAAAHKxLN90X7VqVU2cOFF//fWXZs2apb/++ksNGzZUlSpVNHnyZJ09ezY74wSQRcYYXb58OUOvm7vZzuh03K8GAAByym3fFJGUlKQrV64oISFBxhj5+/tr2rRpGjZsmD755BN16tQpO+IEkEV0sw0AAP7LslzDsmPHDg0cOFBFihTR4MGDVaNGDe3bt08bN27Ur7/+quHDh+u5557LzlgBAAAA5DJZqmGpWrWq9u3bp+bNm2vmzJlq27atXF1d7cbp0aOHXnzxxWwJEkD2mHL/GXm6pt18yxjpStL1/z1c0u9lOyHRogGb8mVvgAAAADfJUsLSsWNH9e7dW0FBQWmOExAQoKSkpCwHBiD7eboaWV3THyfjDbu4bwUAAOS8LCUsw4YNy+44AAAAgFzrxg5sriVezdZ53zi//2JHORlOWIYMGZLhmU6YMCFLwQAAAAC5UUJCgu3/5bun5uhyvL29c2z+OSHDCcvOnTszNJ4lvUbvAAAAAJAJGU5Y1q9fn5NxAAAAOAVjjN1zqZLLkq+Ae3p6pnqB1mq1cuEWWebp6Wn7/+Fq/eXm6p5t876WeNVWa3Pjcv4rbvs5LAAAAHeTrD6/imdS4XbcmOy6ubrLzdUjx5fzX5HlhCU6OlpLlixRbGysrly5Yjfsiy++uO3AAAAAACBLCcvChQvVo0cPNW/eXGvWrFHz5s3122+/6cSJE2rXrl12xwgAAHDHWK1WRUVF2ZXFx8crLCxMkrRs2TJZrdZUpwOQ/bKUsLzzzjuaOHGiBgwYIF9fX02ePFklS5bU008/rSJFimR3jAAAAHeMxWJJt2mX1Wql6RdwB7lkZaKDBw+qTZs2kq7fuHPx4kVZLBYNHjxYH3/8cbYGCAAAACD3ylLC4u/vr/Pnz0uSgoKCtHfvXknSmTNndOnSpeyLDgAAAECulqUmYffdd5/WrFmjKlWq6LHHHtPzzz+vdevWac2aNWrWrFl2xwgAAAAgl8pSwvLhhx/a+id/9dVX5e7uru+//16PPvqohg0blq0BAgAAAMi9spSw+Pv72/53cXHRSy+9pJdeeinbggIAAAAA6TYfHHnq1CmdOnVKSUlJduVVq1a9raCcwZQpUzRlyhQlJiY6OhQAAAAg18pSwrJjxw717NlT+/btkzHGbpjFYrkrTvIHDBigAQMG6Ny5c/Lz83N0OAAAAECulKWE5YknnlC5cuU0c+ZMFS5cWBaLJbvjAgAAAICsJSyHDh3SF198oTJlymR3PAAAAABgk6XnsDRr1ky7d+/O7lgAAAAAwE6WalhmzJihnj17au/evapcubLc3d3thj/88MPZEhwAAACA3C1LCcuWLVv0/fff6+uvv04x7G656R4AAACA42WpSdhzzz2n7t276/jx40pKSrJ7kawAAAAAyC5ZSlji4uI0ePBgFS5cOLvjAQAAAACbLCUsjz76qNavX5/dsQAAAACAnSzdw1KuXDm9+uqr+v7771WlSpUUN90/99xz2RIcAAAAgNwty72E+fj4aOPGjdq4caPdMIvFQsICAAAAIFtk+cGRAAAAAJDTsnQPy42MMTLGZEcsAAAAAGAnywnLp59+qipVqsjLy0teXl6qWrWq5s6dm52xAQAAAMjlstQkbMKECRo2bJgGDhyohg0byhijzZs3q1+/fjp9+rQGDx6c3XECyKIba0ATsvExSTfOi1pWAACQU7KUsHzwwQeaNm2aevToYSsLCwtTpUqVNGLECBIWwIkkJCTY/h+wKX+OLcPb2ztH5g0AAHK3LDUJO378uBo0aJCivEGDBjp+/PhtBwUAAAAAUhZrWMqUKaPFixfrtddesytftGiRypYtmy2BAcgenp6etv+n3P+vPF2zZ74Jif9fY3PjMgAAALJTlhKW8PBwderUSZs2bVLDhg1lsVj0/fffa+3atVq8eHF2xwjgNlgsFtv/nq6SNZsSlrSWAQAAkJ2y1CSsffv22rp1qwoWLKilS5fqiy++UMGCBbVt2za1a9cuu2MEAAAAkEtlqYZFkmrVqqV58+ZlZywAAAAAYCfLCUtSUpJ+//13nTp1SklJSXbD7r///tsODAAAAACylLD8+OOP6tKli44cOZLi+QsWi0WJidn4sAcAAAAAuVaWEpZ+/fqpdu3aWrlypYoUKcINtwAAAAByRJYSlt9++02fffaZypQpk93xAAAAAIBNlhKWevXq6ffffydhAQAA/1nGGMXHx2do3BvHy+g0yaxWK61RgNuQpYTl2Wef1dChQ3XixAlVqVJF7u7udsOrVq2aLcEBAADklPj4eLVo0SLT04WFhWVq/KioKHl5eWV6OQCuy1LC0r59e0lS7969UwzjpnsAAAAA2SVLCcuhQ4eyOw4AAACHeVmSRzrDjaSr//vfXdKtGnhdkTQmG+ICkMWEJSQkRJIUExOj2NhYXblyxTbMYrHYhgMAAPwXeEjyuEUa4pmpOZpbjwIgQ7KUsPzxxx9q166dfv75Z1ksFtuzWJJvKKNJGAAAAIDs4JKViZ5//nmVLFlSJ0+elLe3t/bu3atNmzapdu3a2rBhQzaHCAAAAOQe15Ku6lrilXRfV68lKP7KRcVfuair1xLSHz/p6q0X6sSyVMPyww8/aN26dQoICJCLi4tcXV117733avTo0Xruuee0c+fO7I4TAAAAyBWW75rq6BCcSpZqWBITE+Xj4yNJKliwoI4dOybp+r0t+/fvz77oAAAAAORqWaphqVy5svbs2aNSpUqpXr16Gjt2rDw8PPTxxx+rVKlS2R0jAAAAcFezWq2KiorK8Pjx8fG2ZwItW7ZMVqs1w8v5r8lSwvLGG2/o4sWLkqS33npLDz30kO677z4VKFBAixYtytYAAQAAgLudxWLJ8gNGrVbrXf1w0iwlLDc+FbZUqVKKiYnRP//8o/z589t6CgMAAACA25WlhCU1/v7+2TUrAAAAAJCUxZvuAQAAAOBOIGEBAAAA4LRIWAAAAAA4LRIWAAAAAE6LhAUAAACA0yJhAQAAAOC0SFgAAAAAOC0SFgAAAABOK9seHAnA+SUkWiSZNIcbI11Juv6/h4tksdxqXgAAADmLhAXIRQZsyufoEAAAADKFJmEAAAAAnBY1LDnAmBua3CRezb4Z3zAvu2UA6bBarYqKisrQuPHx8QoLC5MkLVu2TFarNcPLAAAAyAkkLDkgISHB9n+enfNzbBne3t45Mm/cXSwWi7y8vDI9ndVqzdJ0AAAA2YkmYQAAAACcFjUsOcDT09P2/8UaXSRX9+yZceJVW43NjcsAAAAA7lYkLDnAcmNfsK7u2ZewpLUMAAAA4C5FkzAAAAAATouEBQAAAIDTImEBAAAA4LRIWAAAAAA4LRIWAAAAAE6LhAUAAACA0yJhAQAAAOC07vqE5c8//1Tjxo0VGhqqqlWrasmSJY4OCQAAAEAG3fUPjnRzc9OkSZNUvXp1nTp1SjVr1lTr1q2VJ08eR4cGAAAcyBhj+//K9ZJsm/eVNJYDIPPu+oSlSJEiKlKkiCSpUKFC8vf31z///EPCAgBALpeQkGD7f0wOL8fb2zsHlwDc3RzeJGzTpk1q27atihYtKovFoqVLl6YYZ+rUqSpZsqSsVqtq1aql7777LkvL2r59u5KSkhQcHHybUQMAAAC4Exxew3Lx4kVVq1ZNTzzxhNq3b59i+KJFizRo0CBNnTpVDRs21EcffaRWrVopJiZGxYsXlyTVqlXL7ipJsm+++UZFixaVJMXFxalHjx6aMWNGuvEkJCTYzevcuXO3s3oAAMBJeXp62v4fLMkjnXGNpKv/+99dkuUW874iaWIqywGQeQ5PWFq1aqVWrVqlOXzChAl68skn1adPH0nSpEmTFBUVpWnTpmn06NGSpB07dqS7jISEBLVr106vvvqqGjRokO64o0ePVnh4eCbXAgAA/NdYLP+fdkxMZ7zsXA6AzHN4k7D0XLlyRTt27FDz5s3typs3b64tW7ZkaB7GGPXq1UtNmzZV9+7dbzn+q6++qrNnz9pef/75Z5ZiBwAAAHD7HF7Dkp7Tp08rMTFRhQsXtisvXLiwTpw4kaF5bN68WYsWLVLVqlVt98fMnTtXVapUSXV8T09Pqm4BAMgFrFaroqKiMjRufHy8wsLCJEnLli2T1WrN1HIAZJ1TJyzJbq5KNcZkuHr13nvvVVJSUk6EBQAA/sMsFou8vLxSlBtjFB8fn+n5Wa1Wmn8BOcCpE5aCBQvK1dU1RW3KqVOnUtS6AAAAZIf4+Hi1aNEizeHJNS03i4qKSjUBAnB7nPoeFg8PD9WqVUtr1qyxK1+zZs0tb54HAAAA8N/n8BqWCxcu6Pfff7e9P3TokHbt2iV/f38VL15cQ4YMUffu3VW7dm3Vr19fH3/8sWJjY9WvXz8HRg0AAO5Wqd3bYoyxPfbA09Mz1aZf3KsC5AyHJyzbt29XkyZNbO+HDBkiSerZs6ciIiLUqVMnxcXFaeTIkTp+/LgqV66sVatWKSQkxFEhAwCAu1ha97bwtHrAMRyesDRu3FjGmHTH6d+/v/r373+HIgIAAADgLJz6HhYAAAAAuRsJCwAAAACnRcKShilTpig0NFR16tRxdCgAAABArkXCkoYBAwYoJiZG0dHRjg4FAAAAyLVIWAAAAAA4LRIWAAAAAE6LhAUAAACA0yJhAQAAAOC0SFgAAAAAOC0SFgAAAABOi4QFAAAAgNMiYQEAAADgtEhYAAAAADgtEpY0TJkyRaGhoapTp46jQwEAAAByLRKWNAwYMEAxMTGKjo52dCgAAABArkXCAgAAAMBpkbAAAAAAcFokLAAAAACcFgkLAAAAAKdFwgIAAADAaZGwAAAAAHBaJCwAAAAAnJabowO46yVdS3+4Mf8/joubZLFkfV4AAADAXYaEJYfl+SnS0SEAAAAA/1k0CQMAAADgtKhhyQFWq1VRUVEZGjc+Pl5hYWGSpGXLlslqtWZ4GQAAAMDdjoQlDVOmTNGUKVOUmJiY6WktFou8vLwyPZ3Vas3SdAAAAMDdiiZhaRgwYIBiYmIUHR3t6FAAAACAXIuEBQAAAIDTImEBAAAA4LRIWAAAAAA4LW66B3IpY4zi4+Ptym58f/OwZFarVZb0HnAKAACQjUhYgFwqPj5eLVq0SHN4cnfbN4uKiqI3OwAAcMfQJAwAAACA06KGBcilUnvAqTFGCQkJkiRPT89Um37x0FIAAHAnkbAAuVRaDzj19vZ2QDQAAACpo0kYAAAAAKdFwgIAAADAaZGwAAAAAHBaJCwAAAAAnBYJCwAAAACnRcKShilTpig0NFR16tRxdCgAAABArkXCkoYBAwYoJiZG0dHRjg4FAAAAyLVIWAAAAAA4LRIWAAAAAE6LhAUAAACA0yJhAQAAAOC0SFgAAAAAOC0SFgAAAABOi4QFAAAAgNMiYQEAOK3NmzerY8eO2rx5s6NDAQA4CAkLAMApxcfHa/z48Tp58qTGjx+v+Ph4R4cEAHAAEhYAgFOaN2+e4uLiJElxcXGKjIx0cEQAAEcgYQEAOJ2jR48qMjJSxhhJkjFGkZGROnr0qIMjAwDcaSQsAACnYozRxIkT0yxPTmIAALkDCQsAwKkcOXJE0dHRSkxMtCtPTExUdHS0jhw54qDIAACOQMICAHAqISEhqlOnjlxdXe3KXV1dVbduXYWEhDgoMgCAI5CwAACcisVi0eDBg1Nt+jV48GBZLBYHRAUAcBQSFgCA0ylWrJjKly9vV1a+fHkFBQU5KCIAgKOQsKRhypQpCg0NVZ06dRwdCgDkOkePHtW+ffvsymJiYuglDAByIRKWNAwYMEAxMTGKjo52dCgAkKsYYxQeHp7qsPDwcHoJA4BchoQFAOBUDh8+rP3796c6bP/+/Tp8+PCdDQgA4FAkLAAAp/LXX3/d1nAAwN2FhAUA4FQaNGggHx+fVIf5+PioQYMGdzgiAIAjkbAAAJyKi4uLRo4cmeqwt956Sy4u/HQBQG7CUR8A4HRq166tSpUq2ZVVrlxZNWvWdFBEAABHIWEBADil0aNH2x4SabFY9M477zg4IgCAI5CwAACcUr58+dS9e3e5uLioe/fuypcvn6NDAgA4gJujAwAAIC19+vRRnz59HB0GAMCBqGEBAAAA4LRIWAAAAAA4LZqEAQAAAE7KGKP4+PgU5TeWpTbcarXaOi75ryNhAQAAAJxUfHy8WrRoke44YWFhKcqioqLk5eWVU2HdUTQJAwAAAOC0qGEBAAAAnJTValVUVFSKcmOMEhISJEmenp4pmn9ZrdY7Et+dQMICAAAAOCmLxZJm0y5vb+87HI1j0CQMAAAAgNMiYQEAAADgtEhYAAAAADgtEhYAAAAATouEBQAAAIDTImFJw5QpUxQaGqo6deo4OhQAAAAg1yJhScOAAQMUExOj6OhoR4cCAAAA5FokLAAAAACcFgkLAAAAAKdFwgIAAADAaZGwAAAAAHBaJCwAAAAAnBYJCwAAAACnRcICAAAAwGmRsAAAAABwWm6ODiA3McYoPj7eruzG9zcPS2a1WmWxWHI0NgAAAMAZkbDcQfHx8WrRokWaw8PCwlItj4qKkpeXV06FBQAAADgtmoQBAAAAcFrUsNxBVqtVUVFRdmXGGCUkJEiSPD09U236ZbVa70h8AAAAgLMhYbmDLBZLqk27vL29HRANAAAA4PxoEgYAAADAaZGwAAAAAHBaJCwAAAAAnBYJCwAAAACnRcICAAAAwGmRsAAAAABwWiQsAAAAAJwWCQsAAAAAp0XCAgAAAMBpkbAAAAAAcFokLAAAAACcFgkLAAAAAKdFwgIAAADAaZGwpGHKlCkKDQ1VnTp1HB0KAAAAkGtZjDHG0UE4s7Nnzypfvnz6888/lTdvXkeHAwAAANwx586dU3BwsM6cOSM/Pz+HxODmkKX+h5w/f16SFBwc7OBIAAAAAMc4f/68wxIWalhuISkpSceOHZOvr68sFoujwwEAAADuGGOMzp8/r6JFi8rFxTF3k5CwAAAAAHBa3HQPAAAAwGmRsAAAAABwWiQsAAAAAJwWCQsAwOls2LBBFotFZ86ccXQoAAAHI2EBANhs2bJFrq6uatmyZYphI0aMUPXq1VOUWywWLV26NOeDS4fFYkn31atXL4fGBwDIOp7DAgCwmTVrlp599lnNmDFDsbGxKl68uKNDypDjx4/b/l+0aJHefPNN7d+/31bm5eXliLAAANmAGhYAgCTp4sWLWrx4sZ555hk99NBDioiIsA2LiIhQeHi4du/ebau1iIiIUIkSJSRJ7dq1k8Visb0/ePCgwsLCVLhwYfn4+KhOnTr69ttv7ZaXkJCgl156ScHBwfL09FTZsmU1c+bMVGO7fPmy2rRpo3vuuUf//PNPiuGBgYG2l5+fnywWiwIDA1W4cGHde++9+uSTT+zG37t3r1xcXHTw4EFJ12topk2bplatWsnLy0slS5bUkiVL7Kb566+/1KlTJ+XPn18FChRQWFiYDh8+nIktDADIChIWAICk6zUT5cuXV/ny5dWtWzfNnj1byY/q6tSpk4YOHapKlSrp+PHjOn78uDp16qTo6GhJ0uzZs3X8+HHb+wsXLqh169b69ttvtXPnTrVo0UJt27ZVbGysbXk9evTQwoUL9f7772vfvn2aPn26fHx8UsR19uxZNW/eXFeuXNHatWvl7++f4XWyWCzq3bu3Zs+ebVc+a9Ys3XfffSpdurStbNiwYWrfvr12796tbt26qXPnztq3b58k6dKlS2rSpIl8fHy0adMmff/99/Lx8VHLli115cqVDMcDAMgCAwCAMaZBgwZm0qRJxhhjrl69agoWLGjWrFljGz58+HBTrVq1FNNJMl9++eUt5x8aGmo++OADY4wx+/fvN5Ls5n+j9evXG0nm119/NdWqVTOPPvqoSUhIyNB6zJ492/j5+dneHzt2zLi6upqtW7caY4y5cuWKCQgIMBEREXbr0K9fP7v51KtXzzzzzDPGGGNmzpxpypcvb5KSkmzDExISjJeXl4mKispQXACArKGGBQCg/fv3a9u2bXr88cclSW5uburUqZNmzZqVpfldvHhRL730kkJDQ5UvXz75+Pjo119/tdWw7Nq1S66urmrUqFG683nggQdUqlQpLV68WB4eHlmKpUiRImrTpo1tXVasWKH4+Hh17NjRbrz69euneJ9cw7Jjxw79/vvv8vX1lY+Pj3x8fOTv76/4+HhbszIAQM7gpnsAgGbOnKlr164pKCjIVmaMkbu7u/7991/lz58/U/N78cUXFRUVpXHjxqlMmTLy8vJShw4dbM2nMnoTfJs2bfT5558rJiZGVapUyVQMN+rTp4+6d++uiRMnavbs2erUqZO8vb1vOZ3FYpEkJSUlqVatWoqMjEwxTkBAQJbjAgDcGjUsAJDLXbt2TZ9++qnGjx+vXbt22V67d+9WSEiI7STdw8NDiYmJKaZ3d3dPUf7dd9+pV69eateunapUqaLAwEC7G9SrVKmipKQkbdy4Md3Y3n33XfXs2VPNmjVTTExMltexdevWypMnj6ZNm6avv/5avXv3TjHOjz/+mOJ9hQoVJEk1a9bUb7/9pkKFCqlMmTJ2Lz8/vyzHBQC4NRIWAMjlVqxYoX///VdPPvmkKleubPfq0KGDreeuEiVK6NChQ9q1a5dOnz6thIQEW/natWt14sQJ/fvvv5KkMmXK6IsvvrAlPl26dFFSUpJtmSVKlFDPnj3Vu3dvLV26VIcOHdKGDRu0ePHiFPGNGzdOXbt2VdOmTfXrr79maR1dXV3Vq1cvvfrqqypTpkyK5l+StGTJEs2aNUsHDhzQ8OHDtW3bNg0cOFCS1LVrVxUsWFBhYWH67rvvdOjQIW3cuFHPP/+8jh49mqWYAAAZQ8ICALnczJkz9cADD6RaU9C+fXvt2rVLP/30k9q3b6+WLVuqSZMmCggI0IIFCyRJ48eP15o1axQcHKwaNWpIkiZOnKj8+fOrQYMGatu2rVq0aKGaNWvazXvatGnq0KGD+vfvrwoVKqhv3766ePFiqjFOnDhRjz32mJo2baoDBw5kaT2ffPJJXblyJdXaFUkKDw/XwoULVbVqVc2ZM0eRkZEKDQ2VJHl7e2vTpk0qXry4Hn30UVWsWFG9e/fW5cuXlTdv3izFAwDIGIsx/+uzEgCAu9jmzZvVuHFjHT16VIULF7YbZrFY9OWXX+qRRx5xTHAAgDRx0z0A4K6WkJCgP//8U8OGDdNjjz2WIlkBADg3moQBAO5qCxYsUPny5XX27FmNHTvW0eEAADKJJmEAAAAAnBY1LAAAAACcFgkLAAAAAKdFwgIAAADAaZGwAAAAAHBaJCwAAAAAnBYJCwAAAACnRcICAAAAwGmRsAAAAABwWiQsAAAAAJwWCQsAAAAAp0XCAgAAAMBpkbAAAAAAcFokLAAAAACcFgkLAAAAAKdFwgIAAADAaZGwAAAAAHBaJCwAAAAAnBYJCwAAAACnRcICAAAAwGmRsAAAAABwWiQsAAAAAJwWCQsAAAAAp0XCAgAAAMBpkbAAAAAAcFokLAAAAACcFgkLAAAAAKdFwgIAAADAaZGwAAAAAHBaJCwAAAAAnBYJCwAAAACnRcICAAAAwGmRsAAAAABwWiQsAAAAAJwWCQsAAAAAp0XCAgAAAMBpkbAAAAAAcFokLAAAAACcFgkLAAAAAKdFwgIAAADAaZGwAAAAAHBaJCwAAAAAnBYJCwAAAACnRcICAAAAwGmRsAAAAABwWiQsAAAAAJwWCQsAAAAAp+Xm6AAAZ3Pt2jVduXLF0WEAAOCUPDw85ObGKSTuHPY24H+MMYqNjdXp06cdHQoAAE6tYMGCKl68uCwWi6NDQS5AwgL8T3KyEhQUJB8fH7m40GISAIAbJSUl6cKFC/rrr78kSSEhIQ6OCLkBCQug683AkpOVwMBAR4cDAIDT8vHxkST99ddfOnTokOrXry9PT08HR4W7GZeQAcl2z0ryQRgAAKQt+ffy559/1jfffKOEhAQHR4S7GQkLcAOagQEAcGvJv5cFCxbUL7/8ooMHDzo4ItzNODsDAABAlnh4eMgYowsXLjg6FNzFSFiAW0hMTNS1a9fu2CsxMTFT8TVu3FiDBg3KmZW/Qa9evfTII4/k+HKc1YYNG2SxWHTmzBlJUkREhPLly+fQmPD/nP17CjirEiVKaNKkSbc9n6SkpNsPBkgDN90D6UhMTFS7RzvozL9xd2yZ+fIX0JdffCZXV9c7tsyMmDx5sowxjg4DSCExMVEd27XT6f8lk3dCwXz5tOTLLzP8PT116pSGDRumr7/+WidPnlT+/PlVrVo1jRgxQvXr15ck7dy5U8OGDdO2bdt07tw5BQYGql69epoyZYoKFiyow4cPq2TJktq5c6eqV69uN//GjRurevXq6Z54lihRQkeOHJEkeXl5qVSpUnr22Wf19NNPZ2gdRowYoaVLl2rXrl0ZGj9ZRESEBg0aZEv2He2dd97RsGHD9Pbbb+uVV16xG5badtywYYOaNGmif//912kuUpQoUUKDBg26IxerAGdAwgKkwxijM//G6WLtXpLlDlRImiRpe4RTJgZ+fn6ODgFIlTFGp8+c0TBJdyLNT5Q06syZTH1P27dvr6tXr2rOnDkqVaqUTp48qbVr1+qff/6RdD2heeCBB9S2bVtFRUUpX758OnTokJYvX65Lly5lW+wjR45U3759deHCBUVERKhfv37Kly+fOnXqlG3LyCmJiYmyWCy3fa/h7Nmz9dJLL2nWrFkpEhYAzokmYUBGWFwklzvwymJSdO3aNQ0cOFD58uVTgQIF9MYbb9idTF25ckUvvfSSgoKClCdPHtWrV08bNmywDU9u3hQVFaWKFSvKx8dHLVu21PHjx23j3Nwk7Pz58+ratavy5MmjIkWKaOLEiSmap5UoUULvvPOOevfuLV9fXxUvXlwff/xxltbxRrt371aTJk3k6+urvHnzqlatWtq+fbvduqxYsULly5eXt7e3OnTooIsXL2rOnDkqUaKE8ufPr2effdauWc+8efNUu3Zt+fr6KjAwUF26dNGpU6duO1bcOa6SXGW5A6/MOXPmjL7//nuNGTNGTZo0UUhIiOrWratXX31Vbdq0kSRt2bJF586d04wZM1SjRg2VLFlSTZs21aRJk1S8ePFs20bJ+3eZMmX01ltvqWzZslq6dKkk6eWXX1a5cuXk7e2tUqVKadiwYbp69aqk69+r8PBw7d69WxaLRRaLRREREZKkCRMmqEqVKsqTJ4+Cg4PVv39/2/0MGzZs0BNPPKGzZ8/aphsxYoQk6d9//1WPHj2UP39+eXt7q1WrVvrtt99ssd74XQ4NDZWnp6ethiirNm7cqMuXL2vkyJG6ePGiNm3aZBvWq1cvbdy4UZMnT7bFevjwYTVp0kSSlD9/flksFvXq1UvS9UR57NixKlWqlLy8vFStWjV99tlntvklNyONiopSjRo15OXlpaZNm+rUqVP6+uuvVbFiReXNm1edO3e2S0obN26sgQMHpnlMb9y4sY4cOaLBgwfb4ky2ZcsW3X///fLy8lJwcLCee+45Xbx40Tb81KlTatu2rby8vFSyZElFRkbe1vYE7hQSFuAuMGfOHLm5uWnr1q16//33NXHiRM2YMcM2/IknntDmzZu1cOFC7dmzRx07dlTLli3tTg4uXbqkcePGae7cudq0aZNiY2P1wgsvpLnMIUOGaPPmzVq+fLnWrFmj7777Tj/99FOK8caPH6/atWtr586d6t+/v5555hn9+uuvt7W+Xbt2VbFixRQdHa0dO3bolVdekbu7u926vP/++1q4cKFWr16tDRs26NFHH9WqVau0atUqzZ07Vx9//LHdycWVK1c0atQo7d69W0uXLtWhQ4dsJybA7fDx8ZGPj4+WLl2aZtevgYGBunbtmr788ss7WsNqtVptSYmvr68iIiIUExOjyZMn65NPPtHEiRMlSZ06ddLQoUNVqVIlHT9+XMePH7fVyri4uOj999/X3r17NWfOHK1bt04vvfSSJKlBgwaaNGmS8ubNa5su+bjSq1cvbd++XcuXL9cPP/wgY4xat25ti0e6/l0ePXq0ZsyYoV9++UWFChW6rfWdOXOmOnfuLHd3d3Xu3FkzZ860DZs8ebLq16+vvn372mINDg7W559/Lknav3+/jh8/rsmTJ0uS3njjDc2ePVvTpk3TL7/8osGDB6tbt27auHGj3TJHjBihDz/8UFu2bNGff/6pxx57TJMmTdL8+fO1cuVKrVmzRh988IHdNOkd07/44gsVK1ZMI0eOtMUpXe9euEWLFnr00Ue1Z88eLVq0SN9//70GDhxom2+vXr10+PBhrVu3Tp999pmmTp3KhRn8J9AkDLgLBAcHa+LEibJYLCpfvrx+/vlnTZw4UX379tXBgwe1YMECHT16VEWLFpUkvfDCC1q9erVmz56td955R5J09epVTZ8+XaVLl5YkDRw4UCNHjkx1eefPn9ecOXM0f/58NWvWTNL1ZhbJ879R69at1b9/f0nXr+BOnDhRGzZsUIUKFbK8vrGxsXrxxRdt8yhbtqzd8KtXr2ratGm2denQoYPmzp2rkydPysfHR6GhoWrSpInWr19vO+nq3bu3bfpSpUrp/fffV926dXXhwgWez4Pb4ubmpoiICPXt21fTp09XzZo11ahRIz3++OOqWrWqJOmee+7Ra6+9pi5duqhfv36qW7eumjZtqh49eqhw4cJ282vQoEGKZlGXL19OcV9Leq5du6Z58+bp559/1jPPPCPp+gl4shIlSmjo0KFatGiRXnrpJXl5ecnHx0dubm4pHq57Y61qyZIlNWrUKD3zzDOaOnWqPDw85OfnJ4vFYjfdb7/9puXLl2vz5s1q0KCBJCkyMlLBwcFaunSpOnbsKOn6d3nq1KmqVq1ahtctLefOndPnn3+uLVu2SJK6deumhg0b6oMPPlDevHnl5+cnDw8PeXt728Xq7+8vSSpUqJDtHpaLFy9qwoQJWrdune0epFKlSun777/XRx99pEaNGtmmf+utt9SwYUNJ0pNPPqlXX31VBw8eVKlSpSRdPz6tX79eL7/8sm2a9I7p/v7+cnV1tdWWJXvvvffUpUsX2+dRtmxZvf/++2rUqJGmTZum2NhYff311/rxxx9Vr149SdcTuIoVK972tgVyGjUswF3gnnvusWsWUL9+ff32229KTEzUTz/9JGOMypUrZ7vS6+Pjo40bN9r1m+/t7W07wZekIkWKpHnl7Y8//tDVq1dVt25dW5mfn5/Kly+fYtzkEzJJtpOWtOYbGRlpF+N3332X6nhDhgxRnz599MADD+jdd99N0f//zetSuHBhlShRwi7xKFy4sF0cO3fuVFhYmEJCQuTr66vGjRtLup4cAberffv2OnbsmJYvX64WLVpow4YNqlmzpq1ZlSS9/fbbOnHihKZPn67Q0FBNnz5dFSpU0M8//2w3r0WLFmnXrl12r9q1a9uGv/POO3bfoxv34Zdfflk+Pj7y8vLSgAED9OKLL9puuv/ss8907733KjAwUD4+Pho2bFiG9v/169frwQcfVFBQkHx9fdWjRw/FxcXZNUW62b59++Tm5mY7cZakAgUKqHz58tq3b5+tzMPDw+4YkppKlSrZ1rVVq1Zpjjd//nyVKlXKlvxUr15dpUqV0sKFC2+5jjeLiYlRfHy8HnzwQbtt/emnn6Y4Ht0Yf+HChW1N7m4su/mYmN4xPS07duxQRESEXTwtWrRQUlKSDh06ZNvmN+4rFSpUcJqOBID0UMMC3OWSkpLk6uqqHTt2pOjR6MYT+BubVEnXk4u0mqYkl9/4g3pj+Y1Sm29a3V8+/PDDdicwQUFBqY43YsQIdenSRStXrtTXX3+t4cOHa+HChWrXrl2ay0wvjosXL6p58+Zq3ry55s2bp4CAAMXGxqpFixa6cuVKqjEAmWW1WvXggw/qwQcf1Jtvvqk+ffpo+PDhdk0PCxQooI4dO6pjx44aPXq0atSooXHjxmnOnDm2cYKDg1WmTBm7eXt5edn+79evnx577DHb+xtrPl988UX16tVL3t7eKlKkiO07/OOPP+rxxx9XeHi4WrRoIT8/Py1cuFDjx49Pd52OHDmi1q1bq1+/fho1apT8/f31/fff68knn7Rr2nWz9I4tNx5XvLy8UhxnbrZq1Srbsm7cDjebNWuWfvnlF7m5/f+pT1JSkmbOnKmnnnoq3WXcLPnYsXLlyhTHKU9PT7v3Nx57bnUsuh1JSUl6+umn9dxzz6UYVrx4ce3fv9+2POC/hoQFuAv8+OOPKd6XLVtWrq6uqlGjhhITE3Xq1Cndd9992bK80qVLy93dXdu2bVNwcLCk680tfvvtN7umEJnl6+srX1/fDI1brlw5lStXToMHD1bnzp01e/ZsW8KSWb/++qtOnz6td99917Y+yTfxAzklNDTUdsN7ajw8PFS6dOl0aypS4+/vb2vGdLOCBQumSHYkafPmzQoJCdHrr79uK7v5BncPD48UV/i3b9+ua9euafz48bZmaosXL77ldKGhobp27Zq2bt1qaxIWFxenAwcOZLqJUkhIyC3H+fnnn7V9+3Zt2LDBbtucOXNG999/v/bu3avKlSunGquHh4ck2ZUndwIQGxt7W8e8tKR3TE+O6eY4a9asqV9++SXVz1eSKlasqGvXrmn79u222vH9+/c7TXfTQHpoEgbcBf78808NGTJE+/fv14IFC/TBBx/o+eefl3T9xL5r167q0aOHvvjiCx06dEjR0dEaM2aMVq1alaXl+fr6qmfPnnrxxRe1fv16/fLLL+rdu7dcXFxy/Ord5cuXNXDgQG3YsEFHjhzR5s2bFR0dfVvtsIsXLy4PDw998MEH+uOPP7R8+XKNGjUqG6NGbhYXF6emTZtq3rx52rNnjw4dOqQlS5Zo7NixCgsLkyStWLFC3bp104oVK3TgwAHt379f48aN06pVq2zj5KQyZcooNjZWCxcu1MGDB/X+++/ryy+/tBunRIkSOnTokHbt2qXTp08rISFBpUuX1rVr12zfnblz52r69Okpprtw4YLWrl2r06dP69KlSypbtqzCwsLUt29fff/999q9e7e6deumoKCgHFnfmTNnqm7durr//vtVuXJl2+vee+9V/fr1bTfflyhRQlu3btXhw4d1+vRpJSUlKSQkRBaLRStWrNDff/+tCxcuyNfXVy+88IIGDx6sOXPm6ODBg9q5c6emTJliVxuWVekd05Pj3LRpk/766y+dPn1a0vXmfj/88IMGDBigXbt22e4TevbZZyVJ5cuXV8uWLdW3b19t3bpVO3bsUJ8+fdKtlQKcBQkLkBEmSUq6Ay+TtWYBPXr00OXLl1W3bl0NGDBAzz77rF0Th9mzZ6tHjx4aOnSoypcvr4cfflhbt2611SZkxYQJE1S/fn099NBDeuCBB9SwYUNVrFhRVqs1y/PMCFdXV8XFxalHjx4qV66cHnvsMbVq1Urh4eFZnmdAQIAiIiK0ZMkShYaG6t1339W4ceOyMWrcCYmSEmXuwCtzfHx8VK9ePU2cONF2wjxs2DD17dtXH374oaTrV+y9vb01dOhQVa9eXffcc48WL16sGTNmqHv37tm+rW4WFhamwYMHa+DAgapevbq2bNmiYcOG2Y3Tvn17tWzZUk2aNFFAQIAWLFig6tWra8KECRozZowqV66syMhIjR492m66Bg0aqF+/furUqZMCAgI0duxYSdePS7Vq1dJDDz2k+vXryxijVatWpWgydbuuXLmiefPmqX379qkOb9++vebNm6crV67ohRdekKurq0JDQ21NQ4OCghQeHq5XXnlFhQsXtvW6NWrUKL355psaPXq0KlasqBYtWuirr75SyZIlbzvmWx3TR44cqcOHD6t06dIKCAiQdP1emY0bN+q3337Tfffdpxo1amjYsGEqUqSIbbrZs2crODhYjRo10qOPPqqnnnrqtnteA+4Ei3HGJ9QBd9ilS5e0b98+VaxYUd7e3rZynnSfcRcvXlRQUJDGjx+vJ5980tHhIBf5LzzpHsioxo0bq3r16po0aZKjQ0lX8u/m4cOHdeDAATVp0kT33HOPo8PCXYp7WIB0uLq66ssvPrujz0WwWCz/iZOgnTt36tdff1XdunV19uxZWxfId6L5CnAjV1dXLbnDzy/5r3xPAeBuQMIC3AInJWkbN26c9u/fLw8PD9WqVUvfffedChYs6OiwkAvxPQWAuxcJC4AsqVGjhnbs2OHoMADgrrJhwwZHhwA4HW66BwAAAOC0SFgAAAAAOC0SFgAAAABOi4QFAAAAgNMiYQEAAADgtEhYAAAAADgtujUGbiExMZEH0gEZcPjwYZUsWVI7d+5U9erV7+iy+Z4CwN2LhAVIR2Jiojq2f0Sn/zl7x5ZZ0N9PSz5fmuGToV69emnOnDkpyj/55BP17ds33Wlnz56tEiVKqEmTJv+//IIFVbt2bb377ruqVq1aqtMln5gmy5cvn6pUqaJRo0apUaNGGYq7cePGql69uiZNmpSh8ZP16tVLZ86c0dKlSzM1XU5p3ry51q5dq82bN+uee+6xG2axWPTll1/qkUcesZWNGDFCS5cu1a5du+5soGlwZJKRXRITE9X+0Q7659+4O7ZM//wF9PkXn2UqaTl16pSGDRumr7/+WidPnlT+/PlVrVo1jRgxQvXr19fOnTs1bNgwbdu2TefOnVNgYKDq1aunKVOmqGDBgul+Vhn5PpUoUUJHjhyRJHl5ealUqVJ69tln9fTTT2co/qzuuxERERo0aJDOnDmTqekAIBkJC5AOY4xO/3NWM5v8K1dLzi8v0UhPrlemrxS3bNlSs2fPtivLnz+/HnroIdv7559/XufOnbMbz8/PT1u3bpUk7d+/X3nz5lVsbKyee+45tWzZUr/++qv8/PzSXO63336rSpUq6dSpU3rttdfUunVr7d271y6ZcVZXrlyRh4fHbc0jNjZWP/zwgwYOHKiZM2emSFhwZxhj9M+/cXq05iC5WHK+pXOSSdIXP03K9Pe0ffv2unr1qubMmaNSpUrp5MmTWrt2rf755x+dOnVKDzzwgNq2bauoqCjly5dPhw4d0vLly3Xp0qVsi33kyJHq27evLly4oIiICPXr10/58uVTp06dsm0ZOSUxMVEWi0UuLrRmB3IbvvVABrhaJDeXnH9lNSny9PRUYGCg3evmMi8vr1TLkhUqVEiBgYGqW7euxo8frxMnTujHH39Md7kFChRQYGCgqlatqo8++kiXLl3SN998o7i4OHXu3FnFihWTt7e3qlSpogULFtim69WrlzZu3KjJkyfLYrHIYrHo8OHDSkxM1JNPPqmSJUvKy8tL5cuX1+TJk23TjRgxQnPmzNGyZcts0yU/Ffrnn39W06ZN5eXlpQIFCuipp57ShQsX7Jb5yCOPaPTo0SpatKjKlSuXtY19g9mzZ+uhhx7SM888o0WLFunixYu2YSVKlJAktWvXThaLRSVKlFBERITCw8O1e/duW/wRERGSpLNnz+qpp55SoUKFlDdvXjVt2lS7d++2W/fq1atr1qxZKl68uHx8fPTMM88oMTFRY8eOVWBgoAoVKqS3337bLkaLxaJp06apVatW8vLyUsmSJbVkyRLb8OTkskaNGrJYLGrcuLHd+lWsWFFWq1UVKlTQ1KlT7ea9bds21ahRQ1arVbVr19bOnTtve5veDheLi1xcXHP+lYWk6MyZM/r+++81ZswYNWnSRCEhIapbt65effVVtWnTRlu2bNG5c+c0Y8YM1ahRQyVLllTTpk01adIkFS9ePNu2ka+vrwIDA1WmTBm99dZbKlu2rK228uWXX1a5cuXk7e2tUqVKadiwYbp69aokpbvvTpgwQVWqVFGePHkUHBys/v372757GzZs0BNPPKGzZ8/aphsxYoQk6d9//1WPHj2UP39+eXt7q1WrVvrtt99ssUZERChfvnxasWKFQkND5enpaashApC7UMMCIIXkRCb5ZCUjvL29bdPEx8erVq1aevnll5U3b16tXLlS3bt3V6lSpVSvXj1NnjxZBw4cUOXKlTVy5EhJUkBAgJKSklSsWDEtXrxYBQsW1JYtW/TUU0+pSJEieuyxx/TCCy9o3759djVF/v7+unTpklq2bKl77rlH0dHROnXqlPr06aOBAwfaTqokae3atcqbN6/WrFlz2/c7GGM0e/ZsTZkyRRUqVFC5cuW0ePFiPfHEE5Kk6OhoFSpUSLNnz1bLli3l6uoqHx8f7d27V6tXr9a3334r6XotlzFGbdq0kb+/v1atWiU/Pz999NFHatasmQ4cOCB/f39J0sGDB/X1119r9erVOnjwoDp06KBDhw6pXLly2rhxo7Zs2aLevXurWbNmdrU9w4YN07vvvqvJkydr7ty56ty5sypXrqyKFStq27Ztqlu3rq22LLnW6ZNPPtHw4cP14YcfqkaNGtq5c6f69u2rPHnyqGfPnrp48aIeeughNW3aVPPmzdOhQ4f0/PPP39Y2vZv5+PjIx8dHS5cu1T333CNPT0+74YGBgbp27Zq+/PJLdejQQRbLHajSlWS1Wm3fc19fX0VERKho0aL6+eef1bdvX/n6+uqll15Sp06dUt13JcnFxUXvv/++SpQooUOHDql///566aWXNHXqVDVo0ECTJk3Sm2++qf3799u2hXT9IsJvv/2m5cuXK2/evHr55ZfVunVrxcTEyN3dXZJ06dIljR49WjNmzFCBAgVUqFChO7JdADgXEhbgLrBixQrbSYAktWrVyu4qembExcUpPDxcvr6+qlu3boamuXjxol599VW5urqqUaNGCgoK0gsvvGAb/uyzz2r16tVasmSJ6tWrJz8/P3l4eMjb21uBgYG28VxdXRUeHm57X7JkSW3ZskWLFy/WY489Jh8fH3l5eSkhIcFuujlz5ujy5cv69NNPlSdPHknShx9+qLZt22rMmDEqXLiwJClPnjyaMWPGbTcFk643h7t06ZJatGghSerWrZtmzpxpS1gCAgIkXb+/58ZYfXx85ObmZle2bt06/fzzzzp16pTtRHbcuHFaunSpPvvsMz311FOSpKSkJM2aNUu+vr4KDQ1VkyZNtH//fq1atUouLi4qX768xowZow0bNtglLB07dlSfPn0kSaNGjdKaNWv0wQcfaOrUqbY4k2vLko0aNUrjx4/Xo48+avssYmJi9NFHH6lnz56KjIxUYmKiZs2aJW9vb1WqVElHjx7VM888c9vb9m7k5uamiIgI9e3bV9OnT1fNmjXVqFEjPf7446pataruuecevfbaa+rSpYv69eununXrqmnTpurRo4dt/03WoEGDFM2iLl++nKl7kK5du6Z58+bp559/tn1mb7zxhm14iRIlNHToUC1atEgvvfSSvLy8Ut13JWnQoEG2/0uWLKlRo0bpmWee0dSpU+Xh4SE/Pz9ZLBa76ZITlc2bN6tBgwaSpMjISAUHB2vp0qXq2LGjpOsXQKZOnZrm/XQAcgeahAF3gSZNmmjXrl221/vvv5/peRQrVkw+Pj4qWLCg9u3bpyVLlqhQoUJq1aqV7epwpUqV7KZp0KCBfHx85Ovrq6+++koRERGqUqWKEhMT9fbbb6tq1aoqUKCAfHx89M033yg2NvaWcUyfPl21a9dWQECAfHx89Mknn9xyun379qlatWq2ZEWSGjZsqKSkJNtVXUmqUqVKuslKbGysbV19fHz0zjvvpDnuzJkz1alTJ7m5Xb/u07lzZ23dutVueRm1Y8cOXbhwwbatkl+HDh3SwYMHbeOVKFFCvr6+tveFCxdWaGio3clr4cKFderUKbv5169fP8X7ffv2pRnP33//rT///FNPPvmkXTxvvfWWLZ7kbZ5cs5bacmCvffv2OnbsmJYvX64WLVpow4YNqlmzpq0W8O2339aJEyc0ffp0hYaGavr06apQoYJ+/vlnu/ksWrTI7vu+a9cu1a5d2zb8nXfesfvcbvz+vPzyy7bEf8CAAXrxxRdtN91/9tlnuvfeexUYGCgfHx8NGzYsQ9/Z9evX68EHH1RQUJB8fX3Vo0cPxcXF2TWRvNm+ffvk5uamevXq2coKFCig8uXL2+2bHh4eqlq16i1jAHB3o4YFuAvkyZNHZcqUua15fPfdd8qbN68CAgKUN29eW/mMGTN0+fJlSbI100i2aNEihYaGKl++fCpQoICtfPz48Zo4caImTZpka9s+aNAgXblyJd0YFi9erMGDB2v8+PGqX7++fH199d5779k6BkiLMSbNJjQ3lt+Y0KSmaNGidj0gJTfFutk///yjpUuX6urVq5o2bZqtPLnGYcyYMeku52ZJSUkqUqSI7X6cG+XLl8/2/83b32KxpFqWlJR0y2Wm1+QoefpPPvnE7oRSkq1XrDvZhfDdxGq16sEHH9SDDz6oN998U3369NHw4cPVq1cvSddP2jt27KiOHTtq9OjRqlGjhsaNG2fXE2BwcHCK7/uN96P169dPjz32mO190aJFbf+/+OKL6tWrl7y9vVWkSBHbfvDjjz/q8ccfV3h4uFq0aCE/Pz8tXLhQ48ePT3d9jhw5otatW6tfv34aNWqU/P399f333+vJJ59Mt0lpWvvPzd9lLy+vO9Y8DoDzImEBIOl6U44bT46TBQUFpTlNcHCwSpcunaL8u+++U1hYmLp16ybp+gnwb7/9pooVK9rG8fDwUGJiYorpGjRooP79+9vKbqxhSGu60NBQzZkzRxcvXrQlJZs3b5aLi0umbq53c3PLUOIXGRmpYsWKpehaee3atRo9erTefvttubm5yd3dPUWsqcVfs2ZNnThxQm5ubrab9bPTjz/+qB49eti9r1Gjhi0eSXYxFS5cWEFBQfrjjz/UtWvXVOcZGhqquXPn6vLly7aT5Vt10oCUQkND0+yi28PDQ6VLl063piI1/v7+aSbbBQsWTHUf37x5s0JCQvT666/bym6+wT21fXf79u26du2axo8fb6vpW7x48S2nCw0N1bVr17R161Zbk7C4uDgdOHDA7jgBABJNwgDkgDJlymjNmjXasmWL9u3bp6efflonTpywG6dEiRLaunWrDh8+rNOnTyspKUllypTR9u3bFRUVpQMHDmjYsGGKjo5OMd2ePXu0f/9+nT59WlevXlXXrl1ltVrVs2dP7d27V+vXr9ezzz6r7t27p2j/nx1mzpypDh06qHLlynav3r1768yZM1q5cqUt1rVr1+rEiRP6999/bWWHDh3Srl27dPr0aSUkJOiBBx5Q/fr19cgjjygqKkqHDx/Wli1b9MYbb2j79u23He+SJUs0a9YsHThwQMOHD9e2bds0cOBASdd7h/Py8tLq1at18uRJnT17/ZlDI0aM0OjRo20dJPz888+aPXu2JkyYIEnq0qWLXFxc9OSTTyomJkarVq3SuHHjbjvWu1VcXJytg4I9e/bo0KFDWrJkicaOHauwsDCtWLFC3bp104oVK3TgwAHt379f48aN06pVqxQWFpbj8ZUpU0axsbFauHChDh48qPfff19ffvml3Tip7bulS5fWtWvX9MEHH+iPP/7Q3LlzNX369BTTXbhwQWvXrtXp06d16dIllS1bVmFhYerbt6++//577d69W926dVNQUNAdWV8A/y0kLEAGJBrpWlLOvxLvklY2w4YNU82aNdWiRQs1btxYgYGBdg9PlKQXXnhBrq6uCg0NVUBAgGJjY9WvXz89+uij6tSpk+rVq6e4uDi72hZJ6tu3r8qXL2+7z2Xz5s3y9vZWVFSU/vnnH9WpU0cdOnRQs2bN9OGHH2b7uu3YsUO7d+9W+/btUwzz9fVV8+bNNXPmTEnXm8atWbNGwcHBthqN9u3bq2XLlmrSpIkCAgK0YMECWSwWrVq1Svfff7969+6tcuXK6fHHH9fhw4ezJeEKDw/XwoULVbVqVc2ZM0eRkZEKDQ2VdL1W6f3339dHH32kokWL2k4W+/TpoxkzZtjuS2rUqJEiIiJs3SD7+Pjoq6++UkxMjGrUqKHXX389003hsluSSVJSUmLOv8ytm9zdzMfHR/Xq1dPEiRN1//33q3Llyho2bJj69u2rDz/8UKGhofL29tbQoUNVvXp13XPPPVq8eLFmzJih7t2758DWshcWFqbBgwdr4MCBql69urZs2aJhw4bZjZPavlu9enVNmDBBY8aMUeXKlRUZGanRo0fbTdegQQP169dPnTp1UkBAgMaOHSvperfZtWrV0kMPPaT69evLGKNVq1alaOYIABZDQ2RAly5d0r59+1SxYkW7m4j/C0+6B9JjsVj05ZdfpkgY7yb/lSfdA3eT5N/Nw4cP68CBA2rSpAkPz0WO4R4WIB2urq5a8vnSO3qDscVi4SQIyARXV1f9X3t3H1TFdT5w/HuBUN5BeRGigBgVAcWoGANJFC0GlCSAptrUqBSisVjwpTYtOhpk0sa8kAg1iimXF9uMgr9oqjZBwQCDkghiqRhv8KUgjQM4oJgBFITL7w/KlusFUZMKMc9nZv9g95zds8vs3vPsOWfPx/v+T+5TIYR4SEnAIkQ/pFIixOAn96kQQjy8JGARQoiHmPT6FUII8UMng+6FEEIIIYQQg5YELEIIIYQQQohBSwIWIYQQQgghxKAlAYsQQgghhBBi0JKARQghhBBCCDFoScAihBBCCCGEGLQkYBGiHx0dHbS3tz+wpaOjY6BPWQjxIxUeHk5oaOgDP66/vz+rV6/+TvuIi4vj8ccfv2OagTo/IcR3IwGLEHfQ0dFB2PwwZs2a9cCWsPlh9xS0hIeHo1Kp7nlJT08nPz9fZ529vT1z5szhn//8Z5/Hq6qq0skzZMgQpk+fTkFBwV2X+X4rJ1LZED9U3ffpihUr9LZFRUWhUqkIDw/X21ZUVIShoSFBQUF6226/Fy0tLfHy8mLlypWcP3/+juXpzltWVna/p/Sjsn37dtzc3DAxMWHKlCkUFhb2m6egoIApU6ZgYmLCqFGjSE5O1tnu7+/f67M5ODhYSbNjxw68vb2xsrLCysoKX19fPvvsM71jaTQaXnjhBaytrbG0tOTJJ5+kurpa2f7hhx/i7++PlZUVKpWKxsZGnfy3/xb0XEpKSu7xagnx/ZOJI4W4g87OThqvNtIR1vFgwnstNO5vvOfJ/oKCgkhLS1P+bmtrw9DQUJn9e9WqVXz77bc6aaytrTlx4gQAFRUVWFlZUV1dTUxMDEFBQXz99ddYW1v3eczc3Fy8vLy4cuUK69evZ+7cuZw5cwY3N7d7KvtAaGtrw9jYeKCLIX5knJ2d2bNnD++//z6mpqYA3Lx5k927d+Pi4tJrntTUVKKjo0lJSaG6urrXdN33YktLC+Xl5SQmJjJx4kQOHjzIT3/60//pOcHDfz9lZmayevVqtm/fzlNPPcXOnTuZM2cOZ8+e7fP/VllZydy5c1m2bBl//etfOX78OFFRUdjb2zN//nwA9u3bR1tbm5KnoaGBiRMn8rOf/UxZN2LECLZs2cLo0aMByMjIICQkhH/84x94eXkBcPHiRZ5++mkiIyPZvHkz1tbWaDQaTExMlP20tLQQFBREUFAQsbGxeuX18/OjpqZGZ93GjRvJzc3Fx8fnPq+cEN8faWER4m4YPMDlPvzkJz/B0dFRWVxcXBg+fLjyt6mpqV6a7goTgIODA46OjjzxxBMkJCRQW1vLl19+ecdj2tra4ujoiLe3Nzt37qSlpYUjR47Q0NDASy+9xIgRIzAzM2PChAns3r1byRceHk5BQQGJiYnKG7yqqio6OjqIjIzEzc0NU1NT3N3dSUxMVPLFxcWRkZHB3/72NyVffn4+AOXl5cyaNQtTU1NsbW1Zvnw5TU1NOscMDQ3lzTff5NFHH2Xs2LH3d6GF+A4mT56Mi4sL+/btU9bt27cPZ2dnJk2apJe+ubmZrKwsfvWrX/Hcc8+Rnp7e636778VRo0YREhJCbm4u06ZNIzIyss/W2u4XC5MmTUKlUuHv76+z/d1338XJyQlbW1tWrlzJrVu3lG0jR47kjTfeIDw8HGtra5YtWwZ0tQZNnz4dU1NTnJ2diYmJobm5Wcm3fft2xowZg4mJCcOGDePFF1/UOaZWq+W1115j6NChODo6EhcXp7O9urqakJAQLCwssLKyYsGCBdTV1fV6ftDVQr527VpsbGywtbXltddeu+eXQQDvvfcekZGRvPLKK3h4eLB161acnZ3ZsWNHn3mSk5NxcXFh69ateHh48MorrxAREcG7776rpOk+z+4lJycHMzMznYDl+eefZ+7cuYwdO5axY8fyhz/8AQsLC53n84YNG5g7dy5vv/02kyZNYtSoUQQHB+Pg4KCkWb16Nb///e958skney2vsbGxTllsbW05cOAAERERqFSqe75mQnzfJGARQujoDmR6VlD6Y2ZmpuS5efMmU6ZM4dChQ5w5c4bly5ezePFipTUnMTERX19fli1bRk1NDTU1NTg7O6PVahkxYgRZWVmcPXuWTZs2sX79erKysgBYt24dCxYsICgoSMnn5+envDkcMmQIJSUl7N27l9zcXH7961/rlPHo0aNoNBpycnI4dOjQ93GpxGDQ2QntzQOz3Efl95e//KVOS2dqaioRERG9ps3MzMTd3R13d3defvll0tLS7qrCbWBgwKpVq7h06RKlpaW9pikuLga6Wmdqamp0gqi8vDwuXrxIXl4eGRkZpKen6wVL77zzDuPHj6e0tJSNGzdSXl5OYGAg8+bN4/Tp02RmZnLs2DHlPjx58iQxMTHEx8dTUVFBdnY206dP19lnRkYG5ubmnDhxgrfffpv4+HhycnKArtbu0NBQrl69SkFBATk5OVy8eJGFCxf2eR0SEhJITU1FrVZz7Ngxrl69yv79+3XSpKen37FC3tbWRmlpKc8++6zO+meffZaioqI+833xxRd6eQIDAzl58mSfz1a1Ws3Pf/5zzM3Ne93e0dHBnj17aG5uxtfXF+gK8v7+978zduxYAgMDcXBwYNq0aXzyySd9lu1uHDhwgPr6+l67KQoxEKRLmBAPgUOHDmFhYaH8PWfOHPbu3XvP+2loaGDz5s1YWlryxBNP3FWe5uZmYmNjMTQ0ZMaMGQwfPpx169Yp26Ojo8nOzmbv3r1MmzYNa2trjI2NMTMzw9HRUUlnaGjI5s2blb/d3NwoKioiKyuLBQsWYGFhgampKa2trTr5MjIyuHHjBrt27VJ+6Ldt28bzzz/PW2+9xbBhwwAwNzcnJSXloe668qPU0QJZFv2n+19Y0ARGvVcu+7J48WJiY2OVMSTHjx9nz549SmthT2q1mpdffhno6vbZ1NTE0aNHCQgI6Pc448aNA7rGqvR2L9vb2wP/bZ3paciQIWzbtg1DQ0PGjRtHcHAwR48eVVpSAGbNmqVzny9ZsoRf/OIXyti0MWPGkJSUxIwZM9ixYwfV1dWYm5vz3HPPYWlpiaurq16rkre3N6+//rqSf9u2bRw9epTZs2eTm5vL6dOnqaysxNnZGYC//OUveHl5UVJSwtSpU/XOcevWrcTGxipdsJKTkzl8+LBOGmtra9zd3fu8jvX19XR0dCjPkW7Dhg2jtra2z3y1tbW95mlvb6e+vh4nJyedbcXFxZw5cwa1Wq23r/Lycnx9fbl58yYWFhbs378fT09PAK5cuUJTUxNbtmzhjTfe4K233iI7O5t58+aRl5fHjBkz+izjnajVagIDA5VrLcRAk4BFiIfAzJkzdbon9PWGri8jRowAuoKPMWPGsHfvXhwcHJgzZ44yuNTV1ZWvvvpKyePn54eBgQEtLS04OTmRnp7OhAkT6OjoYMuWLWRmZnL58mVaW1tpbW29qzIlJyeTkpLCpUuXuHHjBm1tbf1+9Uej0TBx4kSd/T/11FNotVoqKiqUSsOECRMkWBEDzs7OjuDgYDIyMujs7CQ4OBg7Ozu9dBUVFRQXFystH0ZGRixcuJDU1NS7Cli6W2LupzuPl5eXMv4NwMnJifLycp00t49rKC0t5cKFC3z00Uc6ZdBqtVRWVjJ79mxcXV0ZNWqUMpYiLCxMaZ2FroClJycnJ65cuQJ03efOzs46FWhPT09sbGzQaDR6Acv169epqalRWiKg6xr6+PjotFKFhYURFhbW7zW5/Tp2dnb2e217y9PbeugKEMaPH99rcOnu7k5ZWRmNjY18/PHHLF26lIKCAjw9PdFqtQCEhISwZs0aAB5//HGKiopITk6+r4Dlm2++4fDhw0rrthCDgQQsQjwEzM3NlUGZ96OwsBArKyvs7e2xsrJS1qekpHDjxg0AHnnkEZ08mZmZSoXB1tZWWZ+QkMD777/P1q1bmTBhAubm5qxevVpncGlvsrKyWLNmDQkJCfj6+mJpack777yjdCXry50qDj3X32sQJ34gDM26WjoG6tj3ISIiQukq9cEHH/SaRq1W097ezvDhw5V1nZ2dPPLII1y7do0hQ4bc8RgajQbgvj6Ccfu9rlKplIpxt9vvJ61Wy6uvvkpMTIze/lxcXDA2NubUqVPk5+dz5MgRNm3aRFxcHCUlJdjY2PR73L7u87sJHL4LOzs7DA0N9VpTrly5oteC0pOjo2OveYyMjHSel9A1IH7Pnj3Ex8f3ui9jY2Pl+e7j40NJSQmJiYns3LkTOzs7jIyMlBaXbh4eHhw7duyuz7OntLQ0bG1teeGFF+4rvxD/CxKwCCFwc3NTKg099aws3c7Z2ZnHHntMb31hYSEhISFKVxatVsv58+fx8PBQ0hgbG+sNBi4sLMTPz4+oqChl3cWLF3XS9JbP09OTjIwMmpublUrU8ePHMTAwkMH1PwYq1T13yxpoQUFBSgAfGBiot729vZ1du3aRkJCgNw5i/vz5fPTRR3pjtHrSarUkJSXh5ubW62B+QGlt/L7mfZo8eTJfffXVHV+cGBkZERAQQEBAAK+//jo2NjZ8/vnnzJs3r9/9e3p6Ul1dzb///W+lleXs2bNcv35d59nSzdraGicnJ7788ktlrEx7ezulpaVMnjz5rs/L2NiYKVOmkJOTo9MSk5OTQ0hISJ/5fH19OXjwoM66I0eO4OPjoxeYZWVl0draqjwz+9PZ2Ulra6tSvqlTp1JRUaGT5ty5c7i6ut7V/m7fd1paGkuWLNErpxADSQbdC3E3tA9w+YEbPXo0OTk5FBUVodFoePXVV/XeNI4cOZITJ05QVVVFfX09Wq2W0aNHc/LkSQ4fPsy5c+fYuHGj3vf/R44cyenTp6moqKC+vp5bt26xaNEiTExMWLp0KWfOnCEvL4/o6GgWL158xzegQgwUQ0NDNBoNGo1Gp+tVt0OHDnHt2jUiIyMZP368zvLiiy/qjXNoaGigtraWf/3rXxw4cICAgACKi4tRq9W97h+6vgxoampKdnY2dXV1XL9+/Tud0+9+9zu++OILVq5cSVlZGefPn+fAgQNER0cr55SUlERZWRmXLl1i165daLXaO44f6SkgIABvb28WLVrEqVOnKC4uZsmSJcyYMaPPz+6uWrWKLVu2sH//fr7++muioqL05h/Zv3+/Mt6nL2vXriUlJYXU1FQ0Gg1r1qyhurpaZ06d2NhYlixZovy9YsUKLl26xNq1a9FoNMrg/57jfrqp1WpCQ0P1Wl4A1q9fT2FhIVVVVZSXl7Nhwwby8/NZtGiRkua3v/0tmZmZ/PnPf+bChQts27aNgwcP6rz8qa2tpaysjAsXLgBd42LKysq4evWqzvE+//xzKisriYyMvOM1EeJBkxYWIe5ApVJhM9SGxv2ND+yYNkNtftCfkdy4cSOVlZUEBgZiZmbG8uXLCQ0N1akQrVu3jqVLl+Lp6cmNGzeorKxkxYoVlJWVsXDhQlQqFS+99BJRUVE6k6QtW7aM/Px8fHx8aGpqIi8vD39/fw4fPsyqVauYOnUqZmZmzJ8/n/fee28gTl+Iu9Kz6+Xt1Go1AQEBvc6DNH/+fP74xz9y6tQphg4dCqCMaTEzM8PV1ZWZM2fy4Ycf9tvakZSURHx8PJs2beKZZ57pdeD/3fL29qagoIANGzbwzDPP0NnZyWOPPaZ8xcvGxoZ9+/YRFxfHzZs3GTNmDLt371bmEumPSqXik08+ITo6munTp2NgYEBQUBB/+tOf+szzm9/8hpqaGsLDwzEwMCAiIoKwsDCdZ9H169f1Widut3DhQhoaGoiPj6empobx48fz6aef6rRg1NTU6EzU6ObmxqeffsqaNWv44IMPePTRR0lKSlI+ANDt3LlzHDt2jCNHjvR67Lq6OhYvXkxNTQ3W1tZ4e3uTnZ3N7NmzlTRhYWEkJyfz5ptvEhMTg7u7Ox9//DFPP/20kiY5OVnnoybdrU5paWk6XwJTq9X4+fn12molxEBSdd7PR8mFeMi0tLSg0Wjw8PDQGQQKXV0mHuRtolKp+nwrKoQQQgwG3b+bVVVVnDt3jpkzZ/Y5z4sQ35W0sAjRDwkehBBCCCEGjoxhEUIIIYQQQgxaErAIIYQQQgghBi0JWIQQQgghhBCDlgQsQvRw++RoQgghhNAnv5fiQZKARQj+O4laU9MAzZgthBBC/IB0/17eunVrgEsifgzkK2FC0DUngZ2dHZcvXwbAwsICAwOJ54UQQoietFotTU1NXL58mcbGRmlpEQ+EBCxC/IeLiwuAErQIIYQQoneNjY3U1dUp85R191QQ4n9BAhYh/kOlUuHq6oq5uTnZ2dl8++23ODg4/KBnnRdCCCG+b7du3UKr1dLZ2UldXR3m5ubY29sPdLHEQ0xmuheiF9988w2fffYZDQ0NA10UIYQQYlDq7OzE0tKSgIAAxo0bN9DFEQ8xCViE6MO1a9eor6+nra1toIsihBBCDDpGRkbY2NgwbNiwgS6KeMhJwCKEEEIIIYQYtOQzSEIIIYQQQohBSwIWIYQQQgghxKAlAYsQQgghhBBi0JKARQghhBBCCDFoScAihBBCCCGEGLT+HwW8d1WqHaA/AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Analysis' 'Backdoor' 'Benign' 'DoS' 'Exploits' 'Generic'\n",
      " 'Reconnaissance' 'Shellcode' 'Worms']\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['benign - small' 'DoS GoldenEye - Attempted' 'DoS GoldenEye'\n",
      " 'DoS Hulk - Attempted' 'DoS Hulk' 'DoS Slowhttptest - Attempted'\n",
      " 'DoS Slowhttptest' 'DoS Slowloris - Attempted' 'DoS Slowloris'\n",
      " 'Heartbleed']\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_boxplots(dfs, use_log_scale=True, include_outliers=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "58dd85f3",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_boxplots(dfs, use_log_scale=True, include_outliers=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "de0b9a01",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "from sklearn.metrics import roc_curve, auc\n",
    "\n",
    "import os\n",
    "import pickle\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "\n",
    "# Specify the directory where your pickle files are located\n",
    "directory = '.'  # Replace with the actual directory path\n",
    "\n",
    "# Initialize empty dataframes and a list to store attack types\n",
    "dfs = []\n",
    "attack_types = []\n",
    "\n",
    "# Loop through the files in the directory\n",
    "for filename in os.listdir(directory):\n",
    "    if filename.endswith(\".pkl\"):\n",
    "        # Parse the day and attack type from the filename\n",
    "        parts = filename.split(\"_\")\n",
    "        day = parts[0]\n",
    "        attack_type = parts[1]\n",
    "        attack_types.append(attack_type)\n",
    "        \n",
    "        # Load the pickle file into a dataframe\n",
    "        df = pd.DataFrame({'anomaly_score': pd.read_pickle(os.path.join(directory, filename))})\n",
    "        df['Attack Type'] = attack_type  # Add an 'Attack Type' column\n",
    "        df['Day'] = day  # Add a 'Day' column\n",
    "        dfs.append(df)\n",
    "\n",
    "# Assuming dfs is a list of DataFrames with columns: 'anomaly_score', 'Attack Type', and 'Day'\n",
    "\n",
    "# Combine all DataFrames into one\n",
    "combined_df = pd.concat(dfs, ignore_index=True)\n",
    "\n",
    "# Get unique days\n",
    "unique_days = combined_df['Day'].unique()\n",
    "combined_df['verdict'] = combined_df['Attack Type'].apply(lambda x: 0.0 if 'benign' in x else 1.0)\n",
    "\n",
    "fpr, tpr, threshold = roc_curve(combined_df['verdict'], combined_df['anomaly_score'], pos_label=1)\n",
    "fpr, tpr, threshold = roc_curve(combined_df['verdict'], combined_df['anomaly_score'], pos_label=1)\n",
    "fnr = 1 - tpr\n",
    "eer_threshold = threshold[np.nanargmin(np.absolute((fnr - fpr)))]\n",
    "eer_value = fpr[np.nanargmin(np.absolute((fnr - fpr)))]\n",
    "roc_auc = auc(fpr, tpr)\n",
    "\n",
    "# Plotting the ROC curve\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.plot(fpr, tpr, label=f'ROC Curve (AUC = {roc_auc:.4f})', color='blue')\n",
    "plt.plot([0, 1], [0, 1], linestyle='--', color='gray', label='Random Guessing')\n",
    "\n",
    "plt.xlabel('False Positive Rate (FPR)')\n",
    "plt.ylabel('True Positive Rate (TPR)')\n",
    "plt.title('Receiver Operating Characteristic (ROC) Curve')\n",
    "plt.legend()\n",
    "plt.grid()\n",
    "\n",
    "# Annotation for AUC, EER Value, and EER Threshold at the bottom right\n",
    "plt.text(0.95, 0.05, f'AUC = {roc_auc:.4f}', ha='right', fontsize=10, color='black')\n",
    "plt.text(0.95, 0.1, f'EER Threshold = {eer_threshold:.4f}', ha='right', fontsize=10, color='black')\n",
    "plt.text(0.95, 0.15, f'EER Value = {eer_value:.4f}', ha='right', fontsize=10, color='black')\n",
    "\n",
    "plt.show()"
   ]
  }
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