Secure and Privacy-Preserving Average Consensus
This addresses privacy concerns in distributed systems for applications like information fusion and decentralized control, representing a novel method for a known bottleneck.
The paper tackles the problem of private state information disclosure in average consensus algorithms by proposing a secure and privacy-preserving approach using homomorphic cryptography, achieving exact consensus in a deterministic manner with a lightweight hardware implementation.
Average consensus is fundamental for distributed systems since it underpins key functionalities of such systems ranging from distributed information fusion, decision-making, to decentralized control. In order to reach an agreement, existing average consensus algorithms require each agent to exchange explicit state information with its neighbors. This leads to the disclosure of private state information, which is undesirable in cases where privacy is of concern. In this paper, we propose a novel approach that enables secure and privacy-preserving average consensus in a decentralized architecture in the absence of any trusted third-parties. By leveraging homomorphic cryptography, our approach can guarantee consensus to the exact value in a deterministic manner. The proposed approach is light-weight in computation and communication, and applicable to time-varying interaction topology cases. A hardware implementation is presented to demonstrate the capability of our approach.