ULDP-FL: Federated Learning with Across Silo User-Level Differential Privacy

1 code implementation • 23 Aug 2023 • Fumiyuki Kato, Li Xiong, Shun Takagi, Yang Cao, Masatoshi Yoshikawa

In this study, we present Uldp-FL, a novel FL framework designed to guarantee user-level DP in cross-silo FL where a single user's data may belong to multiple silos.

Federated Learning

Network Shuffling: Privacy Amplification via Random Walks

no code implementations • 8 Apr 2022 • Seng Pei Liew, Tsubasa Takahashi, Shun Takagi, Fumiyuki Kato, Yang Cao, Masatoshi Yoshikawa

However, introducing a centralized entity to the originally local privacy model loses some appeals of not having any centralized entity as in local differential privacy.

OLIVE: Oblivious Federated Learning on Trusted Execution Environment against the risk of sparsification

1 code implementation • 15 Feb 2022 • Fumiyuki Kato, Yang Cao, Masatoshi Yoshikawa

First, we theoretically analyze the leakage of memory access patterns, revealing the risk of sparsified gradients, which are commonly used in FL to enhance communication efficiency and model accuracy.

Federated Learning Inference Attack +1

PCT-TEE: Trajectory-based Private Contact Tracing System with Trusted Execution Environment

1 code implementation • 7 Dec 2020 • Fumiyuki Kato, Yang Cao, Yoshikawa Masatoshi

To this end, we design a TEE-based system with flexible trajectory data encoding algorithms.

Cryptography and Security Computers and Society