Network Consensus with Privacy: A Secret Sharing Method
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Abstract (arXiv)
In this work, inspired by secret sharing schemes, we introduce a privacy-preserving approach for network consensus, by which all nodes in a network can reach an agreement on their states without exposing the individual state to neighbors. With the privacy degree defined for the agents, the proposed method makes the network resistant to the collusion of any given number of neighbors, and protects the consensus procedure from communication eavesdropping. Unlike existing works, the proposed privacy-preserving algorithm is resilient to node failures. When a node fails, the method offers the possibility of rebuilding the lost node via the information kept in its neighbors, even though none of the neighbors knows the exact state of the failing node. Moreover, it is shown that the proposed method can achieve consensus and average consensus almost surely, when the agents have arbitrary privacy degrees and a common privacy degree, respectively. To illustrate the theory, two numerical examples are presented.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 5 Mar 2021.
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Citing papers per year: 2024: 2.
2 papers.
- 2024A survey on secure decentralized optimization and learning16 Aug 2024
- 2024Enhancing Privacy in Federated Learning through Local Training26 Mar 2024