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Resilient Consensus Against Mobile Malicious Agents

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Document pages: 16 pages

Abstract: This paper addresses novel consensus problems in the presence of adversariesthat can move within the network and induce faulty behaviors in the attackedagents. By adopting several mobile adversary models from the computer scienceliterature, we develop protocols which can mitigate the influence of suchmalicious agents. The algorithms follow the class of mean subsequence reduced(MSR) algorithms, under which agents ignore the suspicious values received fromneighbors during their state updates. Different from the static adversarymodels, even after the adversaries move away, the infected agents may remainfaulty in their values, whose effects must be taken into account. We developconditions on the network structures for both the complete and non-completegraph cases, under which the proposed algorithms are guaranteed to attainresilient consensus. Extensive simulations are carried out over random graphsto verify the effectiveness of our approach under uncertainties in the systems.

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