In this post, we talk with Dr. Xiaowei Huang, Dr. Yi Dong, Dr. Mat Weldon, and Dr. Michael Fenton, 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.
In research on PPFL, the protections of a PPFL system are usually encoded in a threat model that defines what kinds of attackers the system can defend against. Some systems assume that attackers will eavesdrop on the system’s operation but won’t be able to affect its operation (a so-called honest but curious attacker), while others assume that attackers may modify or break the system’s operation (an active or fully malicious attacker). Weaker attackers are generally…