[2508.00596] Information-Theoretic Decentralized Secure Aggregation with Passive Collusion Resilience

Computer Science > Information Theory arXiv:2508.00596 (cs) [Submitted on 1 Aug 2025 (v1), last revised 22 Mar 2026 (this version, v4)] Title:Information-Theoretic Decentralized Secure Aggregation with Passive Collusion Resilience Authors:Xiang Zhang, Zhou Li, Shuangyang Li, Kai Wan, Derrick Wing Kwan Ng, Giuseppe Caire View a PDF of the paper titled Information-Theoretic Decentralized Secure Aggregation with Passive Collusion Resilience, by Xiang Zhang and 5 other authors View PDF HTML (experimental) Abstract:In decentralized federated learning (FL), multiple clients collaboratively learn a shared machine learning (ML) model by leveraging their privately held datasets distributed across the network, through interactive exchange of the intermediate model updates. To ensure data security, cryptographic techniques are commonly employed to protect model updates during aggregation. Despite growing interest in secure aggregation, existing works predominantly focus on protocol design and computational guarantees, with limited understanding of the fundamental information-theoretic limits of such systems. Moreover, optimal bounds on communication and key usage remain unknown in decentralized settings, where no central aggregator is available. Motivated by these gaps, we study the problem of decentralized secure aggregation (DSA) from an information-theoretic perspective. Specifically, we consider a network of $K$ fully-connected users, each holding a private input -- an abstractio...