Consensus with Preserved Privacy against Neighbor Collusion

TL;DR

This paper introduces a privacy-preserving consensus algorithm using secret sharing that ensures agents reach agreement without revealing individual states, even under neighbor collusion or eavesdropping.

Contribution

It presents a novel secret sharing-based method that guarantees privacy against colluding neighbors and eavesdroppers during consensus.

Findings

Resistant to any number of colluding neighbors

Protects against eavesdropping during consensus

Ensures privacy until agreement is reached

Abstract

This paper proposes a privacy-preserving algorithm to solve the average consensus problem based on Shamir's secret sharing scheme, in which a network of agents reach an agreement on their states without exposing their individual state until an agreement is reached. Unlike other methods, the proposed algorithm renders the network resistant to the collusion of any given number of neighbors (even with all neighbors' colluding). Another virtue of this work is that such a method can protect the network consensus procedure from eavesdropping.