Efficient Differentially Private Secure Aggregation for Federated Learning via Hardness of Learning with Errors
Authors: Timothy Stevens, Christian Skalka, Christelle Vincent, John Ring, Samuel Clark, Joseph Near | Published: 2021-12-13
プライバシー侵害
Automated Side Channel Analysis of Media Software with Manifold Learning
Authors: Yuanyuan Yuan, Qi Pang, Shuai Wang | Published: 2021-12-09 | Updated: 2021-12-10
Infinitely Divisible Noise in the Low Privacy Regime
Authors: Rasmus Pagh, Nina Mesing Stausholm | Published: 2021-10-13 | Updated: 2022-03-07
Not all noise is accounted equally: How differentially private learning benefits from large sampling rates
Authors: Friedrich Dörmann, Osvald Frisk, Lars Nørvang Andersen, Christian Fischer Pedersen | Published: 2021-10-12
Sharing FANCI Features: A Privacy Analysis of Feature Extraction for DGA Detection
Authors: Benedikt Holmes, Arthur Drichel, Ulrike Meyer | Published: 2021-10-12
The Skellam Mechanism for Differentially Private Federated Learning
Authors: Naman Agarwal, Peter Kairouz, Ziyu Liu | Published: 2021-10-11 | Updated: 2021-10-29
The Connection between Out-of-Distribution Generalization and Privacy of ML Models
Authors: Divyat Mahajan, Shruti Tople, Amit Sharma | Published: 2021-10-07
Privacy and Trust Redefined in Federated Machine Learning
Authors: Pavlos Papadopoulos, Will Abramson, Adam J. Hall, Nikolaos Pitropakis, William J. Buchanan | Published: 2021-03-29 | Updated: 2021-03-30
Failure Modes in Machine Learning Systems
Authors: Ram Shankar Siva Kumar, David O Brien, Kendra Albert, Salomé Viljöen, Jeffrey Snover | Published: 2019-11-25
Effects of Differential Privacy and Data Skewness on Membership Inference Vulnerability
Authors: Stacey Truex, Ling Liu, Mehmet Emre Gursoy, Wenqi Wei, Lei Yu | Published: 2019-11-21