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PrivacyEmerging1 sourceAug 20, 2024 · 12:00via NIST Cybersecurity Insights

Implementation Challenges in Privacy-Preserving Federated Learning

Brief

In this post, we talk with Dr. Xiaowei Huang and Dr. Yi Dong (University of Liverpool), Dr. Mat Weldon ( United Kingdom (UK) Office of National Statistics (ONS)), and Dr. Michael Fenton (Trūata) who were winners in the UK-US Privacy-Enhancing Technologies ( PETs) Prize Challenges.

We discuss implementation challenges of privacy-preserving federated learning (PPFL) - specifically, the areas of threat modeling and real world deployments. Threat Modeling In research on privacy-preserving federated learning (PPFL), the protections of a PPFL system are usually encoded in a threat model that defines

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