Distributed Filtering Design with Enhanced Resilience to Coordinated Byzantine Attacks

TL;DR

This paper introduces a distributed filtering method resilient to coordinated Byzantine attacks by sharing only partial state information, improving robustness and performance in adversarial network environments.

Contribution

The paper presents a novel Byzantine-resilient distributed filter that enhances robustness by partial state sharing and analyzes the impact of attack strategies on network performance.

Findings

Sharing partial states improves robustness against attacks.

Optimal attack design maximizes network MSE.

Performance depends on shared fraction size and covariance design.

Abstract

This paper proposes a Byzantine-resilient consensus-based distributed filter (BR-CDF) wherein network agents employ partial sharing of state parameters. We characterize the performance and convergence of the BR-CDF and study the impact of a coordinated data falsification attack. Our analysis shows that sharing merely a fraction of the states improves robustness against coordinated Byzantine attacks. In addition, we model the optimal attack strategy as an optimization problem where Byzantine agents design their attack covariance or the sequence of shared fractions to maximize the network-wide mean squared error (MSE). Numerical results demonstrate the accuracy of the proposed BR-CDF and its robustness against Byzantine attacks. Furthermore, the simulation results show that the influence of the covariance design is more pronounced when agents exchange larger portions of their states with neighbors. In contrast, the performance is more sensitive to the sequence of shared fractions when smaller portions are exchanged.