Resilient Consensus Against Mobile Malicious Agents

TL;DR

This paper develops resilient consensus protocols capable of mitigating the influence of mobile malicious agents in networks, ensuring reliable agreement despite adversaries that can move and induce faults.

Contribution

It introduces novel algorithms based on MSR techniques that handle mobile adversaries and establishes network conditions guaranteeing resilient consensus.

Findings

Protocols effectively mitigate mobile adversaries' influence.

Network conditions ensure guaranteed resilient consensus.

Simulations confirm robustness under uncertainties.

Abstract

This paper addresses novel consensus problems in the presence of adversaries that can move within the network and induce faulty behaviors in the attacked agents. By adopting several mobile adversary models from the computer science literature, we develop protocols which can mitigate the influence of such malicious agents. The algorithms follow the class of mean subsequence reduced (MSR) algorithms, under which agents ignore the suspicious values received from neighbors during their state updates. Different from the static adversary models, even after the adversaries move away, the infected agents may remain faulty in their values, whose effects must be taken into account. We develop conditions on the network structures for both the complete and non-complete graph cases, under which the proposed algorithms are guaranteed to attain resilient consensus. Extensive simulations are carried out over random graphs to verify the effectiveness of our approach under uncertainties in the systems.