3 citations · 5 across the 6 of their papers we have counts for
4 papers · 1 filter
Hardening Confidential Federated Compute against Side-channel Attacks
James Bell-Clark, Albert Cheu, Adria Gascon +1
In this work, we identify a set of side-channels in our Confidential Federated Compute platform that a hypothetical insider could exploit to circumvent differential privacy (DP) gu…
SNPeek: Side-Channel Analysis for Privacy Applications on Confidential VMs
Ruiyi Zhang, Albert Cheu, Adria Gascon +4
Confidential virtual machines (CVMs) based on trusted execution environments (TEEs) enable new privacy-preserving solutions. Yet, they leave side-channel leakage outside their thre…
Secure Stateful Aggregation: A Practical Protocol with Applications in Differentially-Private Federated Learning
Marshall Ball, James Bell-Clark, Adria Gascon +3
Recent advances in differentially private federated learning (DPFL) algorithms have found that using correlated noise across the rounds of federated learning (DP-FTRL) yields prova…
Confidential Federated Computations
Hubert Eichner, Daniel Ramage, Kallista Bonawitz +11
Federated Learning and Analytics (FLA) have seen widespread adoption by technology platforms for processing sensitive on-device data. However, basic FLA systems have privacy limita…