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publications.html
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<!DOCTYPE HTML>
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<title>SML Publications</title>
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<a href="index.html" class="logo"><strong>SML Lab</strong> Security & Machine Learning</a>
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<h2>Selected Publications</h2>
</header>
<ul class="alt">
<li>
<i>Mateen: Adaptive Ensemble Learning for Network Anomaly Detection</i>,
F. Alotaibi, S. Maffeis.
<b>RAID 2024</b>.
[<a href="https://www.doc.ic.ac.uk/~maffeis/papers/raid24.pdf">PDF</a>]
</li>
<li>
<i>Differentially Private and Adversarially Robust Machine Learning: An Empirical Evaluation</i>,
J. Thakkar, G. Zizzo, S. Maffeis.
<b>PPAI@AAAI 2024</b>.
[<a href="https://arxiv.org/abs/2401.10405">arXiv</a>]
</li>
<li>
<i>Elevating Defenses: Bridging Adversarial Training and Watermarking for Model Resilience</i>,
J. Thakkar, G. Zizzo, S. Maffeis.
<b>DAI@AAAI 2024</b>.
[<a href="https://arxiv.org/abs/2312.14260">arXiv</a>]
</li>
<li>
<i>Rasd: Semantic Shift Detection and Adaptation for Multi-Classification NIDS</i>,
F. Alotaibi, S. Maffeis.
<b>IFIPSEC 2024</b>.
[<a href="https://www.doc.ic.ac.uk/~maffeis/papers/ifipsec24.pdf">PDF</a>]
</li>
<li>
<i>SQIRL: Grey-Box Detection of SQL Injection Vulnerabilities Using Reinforcement Learning</i>,
S. Al Wahaibi, M. Foley, S. Maffeis.
<b>USENIX Security 2023</b>.
[<a href="https://www.doc.ic.ac.uk/~maffeis/papers/usenix23.pdf">PDF</a>]
</li>
<li>
<i>Adaptive Experimental Design for Intrusion Data Collection</i>,
K. Highnam, Z. Hanif, E. Van Vogt, S. Parbhoo, S. Maffeis, N. Jennings.
<b>CAMLIS 2023</b>.
[<a href="https://www.doc.ic.ac.uk/~maffeis/papers/camlis23.pdf">PDF</a>]
</li>
<li>
<i>EarlyCrow: Detecting APT Malware Command and Control Over HTTP(S) Using Contextual Summaries</i>,
A. Alageel, S. Maffeis.
<b>ISC 2022</b>.
[<a href="https://www.doc.ic.ac.uk/~maffeis/papers/isc22.pdf">PDF</a>]
</li>
<li>
<i> HAXSS: Hierarchical Reinforcement Learning for XSS Payload Generation</i>,
M. Foley, S. Maffeis.
<b>IEEE TrustCom 2022</b>.
[<a href="https://www.doc.ic.ac.uk/~maffeis/papers/trustcom22.pdf">PDF</a>]
</li>
<li>
<i> VulBERTa: Simplified Source Code Pre-Training for Vulnerability Detections</i>,
H. Hanif, S. Maffeis.
<b>IEEE IJCNN 2022</b>.
[<a href="https://www.doc.ic.ac.uk/~maffeis/papers/ijcnn22.pdf">PDF</a>]
</li>
<li>
<i>A Hybrid Graph Neural Network Approach for Detecting PHP Vulnerabilities</i>,
R. Rabheru, H. Hanif, S. Maffeis.
<b>IEEE DSC 2022</b>.
[<a href="https://www.doc.ic.ac.uk/~maffeis/papers/dsc22.pdf">PDF</a>]
</li>
<li>
<i>Certified Federated Adversarial Training</i>,
G. Zizzo, A. Rawat, M. Sinn, S. Maffeis, C. Hankin.
<b>NFFL@NeurIPS 2021</b>.
[<a href="https://www.doc.ic.ac.uk/~maffeis/papers/nffl21.pdf">PDF</a>]
</li>
<li>
<i>Hawk-Eye: Holistic Detection of APT Command and Control Domains</i>,
A. Alageel, S. Maffeis.
<b>ACM SAC 2021</b>, (Security Track).
[<a href="https://www.doc.ic.ac.uk/~maffeis/papers/sac21.pdf">PDF</a>]
</li>
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180 Queen's Gate, SW7 2AZ, London.</p>
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