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@@ -129,7 +129,6 @@ <h4>Schedule and Materials</h4>
                     <td>
 			<ol>
 			  		<li><a href="https://oaklandsok.github.io/papers/papernot2018.pdf" target="_blank"> Papernot et al., SoK: Security and Privacy in Machine Learning</a></li>
-			  		<li><a href="https://people.eecs.berkeley.edu/~adj/publications/paper-files/SecML-MLJ2010.pdf" target="_blank">Barreno et al., The security of machine learning</a></li>
 			  		<li><a href="https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.100-2e2023.pdf" target="_blank">Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations</a></li>
 
 			</ol>
@@ -177,7 +176,7 @@ <h4>Schedule and Materials</h4>
                 <tr>
                     <td>5</td>
                     <td>Membership Inference</td>
-                    <td><a href= "#"></a></td>
+                    <td><a href= "https://drive.google.com/file/d/1c755aTE-BxQof1PKQYdHpZmFOyAkP7f3/view?usp=sharing">Slides</a></td>
                     <td>
 			<ol>
 			  		<li><a href="https://arxiv.org/pdf/1610.05820.pdf" target="_blank">Shokri et al., Membership Inference Attacks against Machine Learning Models</a></li>