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<!doctype html>
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<title>Clement Fung's Page</title>
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Clement Fung
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PhD Student <br>
Carnegie Mellon University
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Misc </a>
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<h3> Selected Publications </h3>
<hr border-color="black">
<br>
<p>
<b>Targeted Image Transformation for Improving Robustness in Long Range Aircraft Detection</b> <br>
Rebecca Martin, <u>Clement Fung</u>, Nikhil Keetha, Lujo Bauer, Sebastian Scherer.<br>
<i><a href="https://iros2024-abudhabi.org/">2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024)</a></i><br>
Abu Dhabi, UAE. October 2024. <br>
[<a href="gallery/papers/iros24-robust-aircraft-detection.pdf">PDF</a>]
[<a href="https://ieeexplore.ieee.org/document/10801304">IEEE</a>]
</p>
<br>
<p>
<b>Attributions for ML-based ICS Anomaly Detection: From Theory to Practice</b> <br>
<u>Clement Fung</u>, Eric Zeng, Lujo Bauer.<br>
<i><a href="https://www.ndss-symposium.org/ndss2024/">31st Network and Distributed System Security Symposium (NDSS 2024)</a></i><br>
San Diego, CA, USA. February 2024. <br>
[<a href="gallery/papers/ndss24-ics-anomaly-attribution.pdf">PDF</a>]
[<a href="https://youtu.be/vLmO3Ii4sDA?si=k8DBKLQcBOt8uGD3&t=42">Video</a>]
[<a href="gallery/slides/ndss2024-slides.pdf">Slides</a>]
[<a href="https://github.com/pwwl/ics-anomaly-attribution">Code</a>]
</p>
<br>
<p>
<b>Perspectives from a Comprehensive Evaluation of Reconstruction-based Anomaly Detection in Industrial Control Systems</b> <br>
<u>Clement Fung</u>, Shreya Srinarasi, Keane Lucas, Hay Bryan Phee, Lujo Bauer.<br>
<i><a href="https://esorics2022.compute.dtu.dk/">27th European Symposium on Research in Computer Security (ESORICS 2022)</a></i><br>
Copenhagen, Denmark. September 2022. <br>
[<a href="gallery/papers/esorics2022-ics-anomaly-detection.pdf">PDF</a>]
[<a href="https://link.springer.com/chapter/10.1007/978-3-031-17143-7_24">Springer</a>]
[<a href="https://www.youtube.com/watch?v=vHbY7HsBUKQ">Video</a>]
[<a href="gallery/slides/esorics22-slides.pdf">Slides</a>]
[<a href="https://github.com/pwwl/ics-anomaly-detection">Code</a>]
</p>
<br>
<p>
<b>Biscotti: A Ledger for Private and Secure Peer-to-Peer Machine Learning</b> <br>
Muhammad Shayan, <u>Clement Fung</u>, Chris J.M. Yoon, Ivan Beschastnikh.<br>
<i><a href="https://www.computer.org/csdl/journal/td">IEEE Transactions on Parallel and Distributed Systems (TPDS)</a></i><br>
Volume 32, Issue 7. July 2021. <br>
[<a href="gallery/papers/tpds2020-biscotti.pdf">PDF</a>]
[<a href="https://ieeexplore.ieee.org/document/9292450">IEEE</a>]
[<a href="https://github.com/DistributedML/Biscotti">Code</a>]
</p>
<ul>
<li><p>
A full version of this paper is <a href="https://arxiv.org/abs/1811.09904">available on arXiv</a>.
</p></li>
</ul>
<br>
<p>
<b>Towards a Lightweight, Hybrid Approach for Detecting DOM XSS Vulnerabilities with Machine Learning</b>
<br>
William Melicher, <u>Clement Fung</u>, Lujo Bauer, Limin Jia.<br>
<i><a href="https://www2021.thewebconf.org/">The Web Conference 2021</a></i><br>
Ljubjana, Slovenia (Virtual). April 2021. <br>
[<a href="gallery/papers/www2021-domxss-ml.pdf">PDF</a>]
[<a href="https://www.youtube.com/watch?v=RaEGCln9mg0">Video</a>]
[<a href="https://github.com/pwwl/www-dom-xss-tools">Code</a>]
</p>
<br>
<p>
<b>The Limitations of Federated Learning in Sybil Settings</b> <br>
<u>Clement Fung</u>, Chris J.M. Yoon, Ivan Beschastnikh.<br>
<i><a href="https://raid2020.org/">23rd International Symposium on Research in Attacks, Intrusions and Defenses
(RAID 2020)</a></i><br>
Donostia/San Sebastian, Spain (Virtual). October 2020.<br>
[<a href="gallery/papers/raid20-fl-sybils.pdf">PDF</a>]
[<a href="https://www.youtube.com/watch?v=NSuFm97ipX0">Video</a>]
[<a href="gallery/slides/raid2020-FoolsGold.pdf">Slides</a>]
[<a href="https://github.com/DistributedML/FoolsGold">Code</a>]
</p>
<ul>
<li>
A longer paper describing the FoolsGold algorithm is <a href="https://arxiv.org/pdf/1808.04866.pdf">available on arXiv</a>.
</li>
<li>
<p>This work was featured on an episode of the <a href="https://podcasts.apple.com/us/podcast/sybil-attacks-on-federated-learning/id890348705?i=1000498506776">Data Skeptic Podcast</a>!
</p>
</li>
</ul>
<br>
<p>
<b>Brokered Agreements in Multi-Party Machine Learning</b> <br>
<u>Clement Fung</u>, Ivan Beschastnikh.<br>
<i><a href="https://icsr.zju.edu.cn/apsys2019/">
10th ACM SIGOPS Asia-Pacific Workshop on Systems (APSys 2019)</a></i><br>
Hangzhou, China. August 2019.<br>
[<a href="gallery/papers/apsys19-brokered-ml.pdf">PDF</a>]
[<a href="https://dl.acm.org/citation.cfm?id=3343744">ACM</a>]
[<a href="gallery/slides/ApSys2019-08-19-2019-Final.pdf">Slides</a>]
[<a href="https://github.com/DistributedML/TorML">Code</a>]
</p>
<ul>
<li><p>
A longer paper describing the TorMentor system is <a href="https://arxiv.org/pdf/1811.09712.pdf">available on arXiv</a>.</p>
</li>
</ul>
<br>
<p>
<b>GainForest: Scaling Climate Finance for Forest Conservation using
Interpretable Machine Learning on Satellite Imagery</b> <br>
David Dao, Catherine Cang, <u>Clement Fung</u>, Ming Zhang, Nick Pawlowski, Reuven Gonzales, Nick Beglinger, Ce Zhang.<br>
<i><a href="https://www.climatechange.ai/ICML2019_workshop.html">
Climate Change: How Can AI Help?: ICML 2019 Workshop</a></i><br>
Long Beach, CA, USA. June 2019. <br>
[<a href="gallery/papers/icml2019-gainforest.pdf">PDF</a>]
[<a href="gallery/posters/gainforest-icml19.pdf">Poster</a>]
</p>
<h3> Pre-prints </h3>
<hr border-color="black">
<br>
<p>
<b>Model Selection of Anomaly Detectors in the Absence of Labeled Validation Data</b> <br>
<u>Clement Fung</u>, Chen Qiu, Aodong Li, Maja Rudolph.<br>
arXiv preprint 2310.10461, October 2023.<br>
[<a href="https://arxiv.org/abs/2310.10461">PDF</a>]
</p>
<br>
<p>
<b>Dancing in the Dark: Private Multi-Party Machine Learning in an Untrusted Setting</b> <br>
<u>Clement Fung</u>, Jaime Koerner, Stewart Grant, Ivan Beschastnikh.<br>
arXiv preprint 1811.09712, November 2018.<br>
[<a href="https://arxiv.org/abs/1811.09712">PDF</a>]
[<a href="https://github.com/DistributedML/TorML">Code</a>]
</p>
<br>
<p>
<b>Mitigating Sybils in Federated Learning Poisoning</b> <br>
<u>Clement Fung</u>, Chris J.M. Yoon, Ivan Beschastnikh.<br>
arXiv preprint 1808.04866, August 2018.<br>
[<a href="https://arxiv.org/abs/1808.04866">PDF</a>]
[<a href="https://github.com/DistributedML/FoolsGold">Code</a>]
</p>
<!-- <h3> Posters </h3>
<hr border-color="black">
<br>
<p>
<b>Biscotti: A Ledger for Private and Secure Peer-to-Peer Machine Learning </b><br>
Muhammad Shayan, <u>Clement Fung</u>, Chris J.M. Yoon, Ivan Beschastnikh.<br>
<i><a href="https://www.usenix.org/conference/nsdi19/poster-session">NSDI 2019 Poster Session</a></i><br>
Boston, MA, USA. February 2019.<br>
[<a href="gallery/posters/biscotti-nsdi19.pdf">PDF</a>]
</p> -->
<h3> Talks Given </h3>
<hr border-color="black">
<br>
<p>
<b>Approaches for More Effective ML-based Anomaly Detection in Industrial Control Systems</b> <br>
<ul>
<li>Secure Cyber-Physical Systems Group, CISPA Helmholtz Center for Information Security. October 2024.</li>
<li>SysNets Seminar, Max Planck Institute for Software Systems. October 2024.</li>
<li>Artificial Intelligence and Security Group, Karlsruhe Institute of Technology. October 2024.</li>
<li>CAE-R Research Symposium, National Cybersecurity Education Colloquium. October 2024.</li>
</ul>
</p>
<p>
<b>Attributions for ML-based ICS Anomaly Detection: From Theory to Practice</b> <br>
<ul>
<li>Network and Distributed System Security Symposium (NDSS). February 2024.</a> [<a href="https://youtu.be/vLmO3Ii4sDA?si=k8DBKLQcBOt8uGD3&t=42">Video</a>] </li>
</ul>
</p>
<p>
<b>Perspectives from a Comprehensive Evaluation of Reconstruction-based Anomaly Detection in Industrial Control Systems</b> <br>
<ul>
<!-- <i><a href="https://www.caecommunity.org/community-of-practice/cyber-research/get-know-your-fellow-cae-r">Center of Academic Excellence in Cyber Research (CAE-R) Seminar</a></i>,
Virtual, USA. April 2023.<br> -->
<li><a href="https://www.caecommunity.org/community-of-practice/cyber-research/get-know-your-fellow-cae-r">CAE-R Seminar</a>, April 2023. [<a href="https://drive.google.com/file/d/1nK05uYPnj0GWv48I676JJEBtwzN4gKzN/view?usp=sharing&t=4184">Video</a>] </li>
<li>European Symposium on Research in Computer Security (ESORICS). September 2022.</a> [<a href="https://www.youtube.com/watch?v=vHbY7HsBUKQ">Video</a>] </li>
</ul>
</p>
<p>
<b> Detecting and Explaining Anomalies in Industrial Control </b> <br>
<ul>
<li>Bosch Center for Artificial Intelligence. June 2023.</li>
<li>Accountable Systems Lab, CMU. November 2022.</li>
<li><a href="https://www.cylab.cmu.edu/events/partners_conference/2022/index.html">CyLab Partners Conference</a>. October 2022.</li>
</ul>
</p>
<p>
<b>Towards a Lightweight, Hybrid Approach for Detecting DOM XSS Vulnerabilities with Machine Learning</b> <br>
<ul>
<li>The Web Conference. April 2021.</a> [<a href="https://www.youtube.com/watch?v=RaEGCln9mg0">Video</a>] </li>
</ul>
</p>
<p>
<b>The Limitations of Federated Learning in Sybil Settings</b> <br>
<ul>
<li>Symposium on Research in Attacks, Intrusions and Defenses (RAID). October 2020.</a> [<a href="https://www.youtube.com/watch?v=NSuFm97ipX0">Video</a>] </li>
</ul>
</p>
<p>
<b> Brokered Agreements in Multi-Party Machine Learning </b> <br>
<ul>
<li>Asia-Pacific Workshop on Systems (APSys). August 2019.</li>
</ul>
</p>
<p>
<b> Dancing in the Dark: Private Multi-Party Machine Learning in an Untrusted Setting </b> <br>
<ul>
<li><a href="http://blogs.ubc.ca/cybersecuritysummit/">UBC Cybersecurity Summit</a></i>. May 2018. [<a href="https://youtu.be/rV6U-jy8e1k?t=1h13m30s">Video</a>]</li>
<li>Computer Systems Lab Seminar, University of Toronto. December 2017.</li>
</ul>
</p>
<br>
</div>
</div>
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