Anomaly detection project utilizing CESNET-TimeSeries24 real-world network traffic data. Employs n_flows for comprehensive EDA, SARIMAX modeling, and LSTM-based forecasting to identify anomalous network behaviors. Focuses on time series analysis for robust detection
data-science machine-learning ai deep-learning time-series signal-processing ml intrusion-detection research-project network-analysis unsupervised-learning cesnet cyber-security network-traffic statistical-models network-security anomaly-detection real-world-data timeseries-analysis cesnet-timeseries24
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Updated
Dec 31, 2025 - Jupyter Notebook