2 papers
cs.CR2024
Samplable Anonymous Aggregation for Private Federated Data Analysis
Kunal Talwar, Shan Wang, Audra McMillan +34
We revisit the problem of designing scalable protocols for private statistics and private federated learning when each device holds its private data. Locally differentially private…
cs.CR2024
PINE: Efficient Norm-Bound Verification for Secret-Shared Vectors
Guy N. Rothblum, Eran Omri, Junye Chen +1
Secure aggregation of high-dimensional vectors is a fundamental primitive in federated statistics and learning. A two-server system such as PRIO allows for scalable aggregation of…