Update publications.html

Author: sergiomaffeis

publications.html

@@ -38,6 +38,55 @@ <h2>Selected Publications</h2>
 				</header>
 
 				<ul class="alt">
+					<li>
+						<i>Deep Learning from Imperfectly Labeled Malware Data.</i>,
+						F. Alotaibi, E. Goodbrand, S. Maffeis. 
+						<b>CCS 2025</b>.
+						[Coming soon]
+					</li>
+					<li>
+						<i>KnowML: Improving Generalization of ML-NIDS with Attack Knowledge Graphs.</i>,
+						X. Guo, A. Merono Penuela, S. Maffeis, F. Pierazzi. 
+						<b>arXiv 2025</b>.
+						[<a href="https://www.arxiv.org/pdf/2506.19802">arXiv</a>]
+					</li>
+					<li>
+						<i>APIRL: Deep Reinforcement Learning for REST API Fuzzing.</i>,
+						M. Foley, S. Maffeis. 
+						<b>AAAI 2025</b>.
+						[<a href="papers/aaai25.pdf">PDF</a>]
+					</li>
+					<li>
+						<i>Investigation of Advanced Persistent Threats Network-based Tactics, Techniques and Procedures</i>,
+						A. Alageel, S. Maffeis. 
+						<b>arXiv 2025</b>.
+						[<a href="https://arxiv.org/pdf/2502.08830">arXiv</a>]
+					</li>
+					<li>
+						<i>Detecting APT Malware Command and Control over HTTP(S) Using Contextual Summaries</i>,
+						A. Alageel, S. Maffeis. 
+						<b>arXiv 2025</b>.
+						[<a href="https://arxiv.org/pdf/2502.05367">arXiv</a>]
+					</li>
+					<li>
+						<i>Helping LLMs Improve Code Generation Using Feedback from Testing and Static Analysis</i>,
+						G. Dolcetti, V. Arceri, E. Iotti, S. Maffeis, A. Cortesi, E. Zaffanella. 
+						<b>arXiv 2024</b>.
+						[<a href="https://arxiv.org/pdf/2412.14841">arXiv</a>]
+					</li>
+					<li>
+						<i>HarmLevelBench: Evaluating Harm-Level Compliance and the Impact of Quantization on Model Alignment</i>,
+						Y. Belkhiter, G. Zizzo, S. Maffeis. 
+						<b>SafeGenAI@NeurIPS 2024</b>.
+						[<a href="https://arxiv.org/pdf/2411.06835">arXiv</a>]
+					</li>
+					
+					<li>
+						<i>MED: Exploring LLM Memorization on Encrypted Data</i>,
+						P. Christodoulou, G. Zizzo, S. Maffeis. 
+						<b>SafeGenAI@NeurIPS 2024</b>.
+						[Coming soon]
+					</li>
 					<li>
 						<i>Mateen: Adaptive Ensemble Learning for Network Anomaly Detection</i>,
 						F. Alotaibi, S. Maffeis.