Privacy Preservation with Decentralized Authentication in Multi-Agent Systems
Puspanjali Ghoshal, Charan Annadurai, Axel Sikora, Ashok Singh Sairam · 2024
Multi-Agent Systems (MASs) involve agents transmitting data to a fusion center for aggregation and processing. To preserve the privacy of sensitive information while maintaining data utility, we propose a noise-based privacy-preserving mechanism. Additionally, we introduce a decentralized mutual authentication mechanism that allows agents to authenticate with the fusion center without revealing their identities. The approach leverages Decentralized Identifiers (DIDs) and blockchains to issue and manage Self-Sovereign Identities (SSIs). We validate our approach with a proof-of-concept implementation.