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USENIX Security '17 - Differential Privacy: From Theory to Deployment
Tight Accounting in the Shuffle Model of Differential Privacy
USENIX Security '24 - Privacy Side Channels in Machine Learning Systems
Are We There Yet Timing and Floating-Point Attacks on Differential Privacy Systems
USENIX Security '23 - A Hybrid Alias Analysis and Its Application to Global Variable Protection...
USENIX Security '22 - How to Abuse and Fix Authenticated Encryption Without Key Commitment
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Last Updated: October 27, 2026
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Brendan Avent and Aleksandra Korolova, University of Southern California; David Zeber and Torgeir Hovden, Mozilla; Benjamin ... Tianhao Wang, Jeremiah Blocki, and Ninghui Li, Purdue University; Somesh Jha, University of Wisconsin Madison Protocols ... Abhradeep Guha Thakurta, Assistant Professor, University of California, Santa Cruz Machine learning has fundamentally ... A Google TechTalk, presented by Mikko Heikkilä, University of Helsinki, at the 2021 Google Federated Learning and Analytics ... A Linear Reconstruction Approach for Attribute Inference Attacks against Synthetic Data Meenatchi Sundaram Muthu Selva ... Giuseppe Petracca, The Pennsylvania State University, US; Ahmad-Atamli Reineh, University of Oxford, UK; Yuqiong Sun, The ... Are We There Yet? Timing and Floating-Point Attacks on
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