Perspectives from a Comprehensive Evaluation of Reconstruction-based Anomaly Detection in Industrial Control Systems
Clement Fung, Shreya Srinarasi, Keane Lucas, Hay Bryan Phee, Lujo Bauer.
27th European Symposium on Research in Computer Security (ESORICS 2022)
Copenhagen, Denmark. September 2022. To appear.
Biscotti: A Ledger for Private and Secure Peer-to-Peer Machine Learning
Muhammad Shayan, Clement Fung, Chris J.M. Yoon, Ivan Beschastnikh.
IEEE Transactions on Parallel and Distributed Systems (TPDS)
Volume 32, Issue 7. July 2021.
[PDF] [IEEE Link] [Code]
A full version of this paper is available on arXiv.
Towards a Lightweight, Hybrid Approach for Detecting DOM XSS Vulnerabilities with Machine Learning
William Melicher, Clement Fung, Lujo Bauer, Limin Jia.
The Web Conference 2021
Ljubjana, Slovenia (Virtual). April 2021.
[PDF] [Code] [Video]
The Limitations of Federated Learning in Sybil Settings
Clement Fung, Chris J.M. Yoon, Ivan Beschastnikh.
23rd International Symposium on Research in Attacks, Intrusions and Defenses (RAID 2020)
Donostia/San Sebastian, Spain (Virtual). October 2020.
[PDF] [Slides] [Video] [Code]
This work was also featured on an episode of the Data Skeptic Podcast!
Brokered Agreements in Multi-Party Machine Learning
Clement Fung, Ivan Beschastnikh.
10th ACM SIGOPS Asia-Pacific Workshop on Systems (APSys 2019)
Hangzhou, China. August 2019.
[PDF] [Slides] [ACM Link] [Code]
A longer paper describing the TorMentor system is available on arXiv.
GainForest: Scaling Climate Finance for Forest Conservation using
Interpretable Machine Learning on Satellite Imagery
David Dao, Catherine Cang, Clement Fung, Ming Zhang, Nick Pawlowski, Reuven Gonzales, Nick Beglinger, Ce Zhang.
Climate Change: How Can AI Help?: ICML 2019 Workshop
Long Beach, CA. June 2019.
Dancing in the Dark: Private Multi-Party Machine Learning in an Untrusted Setting
University of Toronto, Toronto, ON. December 2017.