2 papers
cs.CR2026
PRA-TLS: Attestation of a Client Application for TEE
Reina Sasaki, Yutaka Ishikawa, Atsuko Takefusa +1
Trusted Execution Environments (TEEs) are secure foundations for protecting sensitive information and executing computations over confidential data. Processing in an isolated execu…
cs.CR2022
Measuring Lower Bounds of Local Differential Privacy via Adversary Instantiations in Federated Learning
Marin Matsumoto, Tsubasa Takahashi, Seng Pei Liew +1
Local differential privacy (LDP) gives a strong privacy guarantee to be used in a distributed setting like federated learning (FL). LDP mechanisms in FL protect a client's gradient…