Secure Distributed Consensus Estimation under False Data Injection Attacks: A Defense Strategy Based on Partial Channel Coding

TL;DR

This paper addresses false data injection attacks in distributed estimation by analyzing vulnerabilities and proposing defense strategies using partial channel coding and distance-based detection, enhancing security while managing costs.

Contribution

It introduces a novel security analysis framework and two defense mechanisms, including a coding scheme with time-varying matrices, to protect distributed estimation systems from stealthy attacks.

Findings

System vulnerabilities are characterized by necessary and sufficient conditions.

The proposed coding scheme with time-varying matrices effectively mitigates attack risks.

Numerical simulations validate the theoretical security enhancements.

Abstract

This article investigates the security issue caused by false data injection attacks in distributed estimation, wherein each sensor can construct two types of residues based on local estimates and neighbor information, respectively. The resource-constrained attacker can select partial channels from the sensor network and arbitrarily manipulate the transmitted data. We derive necessary and sufficient conditions to reveal system vulnerabilities, under which the attacker is able to diverge the estimation error while preserving the stealthiness of all residues. We propose two defense strategies with mechanisms of exploiting the Euclidean distance between local estimates to detect attacks, and adopting the coding scheme to protect the transmitted data, respectively. It is proven that the former has the capability to address the majority of security loopholes, while the latter can serve as an additional enhancement to the former. By employing the time-varying coding matrix to mitigate the risk of being cracked, we demonstrate that the latter can safeguard against adversaries injecting stealthy sequences into the encoded channels. Hence, drawing upon the security analysis, we further provide a procedure to select security-critical channels that need to be encoded, thereby achieving a trade-off between security and coding costs. Finally, some numerical simulations are conducted to demonstrate the theoretical results.