SAFE: Secure Aggregation with Failover and Encryption
We propose, analyze, and experimentally evaluate a novel secure aggregation algorithm targeted at cross-organizational federated learning applications with a fixed set of participating learners. Our solution organizes learners in a chain and encrypts all traffic to reduce the controller of the aggregation to a mere message broker. We show that our algorithm scales better and is less resource demanding than existing solutions, while being easy to implement on constrained platforms. With 36 nodes, our method outperforms state-of-the-art secure aggregation by 70x, and 56x with and without failover, respectively.
Authors
- Thomas Sandholm (ORCID: https://orcid.org/0000-0003-0554-3584)
- Sayandev Mukherjee (ORCID: https://orcid.org/0000-0002-0472-2145)
- Bernardo A. Huberman (ORCID: https://orcid.org/0000-0002-6783-0864)
Publication Details
- Journal
- ACM Transactions on Modeling and Performance Evaluation of Computing Systems
- Published
- 2025-02-07
- DOI
- https://doi.org/10.1145/3716630
- Citations
- 6
- Primary Topic
- Privacy-Preserving Technologies in Data
- Type
- article
- Field-Weighted Citation Impact
- 7.44