Visible to the public Exploiting an Adversary’s Intentions in Graphical Coordination Games

TitleExploiting an Adversary’s Intentions in Graphical Coordination Games
Publication TypeConference Paper
Year of Publication2020
AuthorsCollins, B. C., Brown, P. N.
Conference Name2020 American Control Conference (ACC)
Date PublishedJuly 2020
ISBN Number978-1-5386-8266-1
Keywordsadversarial behavior, adversarial intent, Adversary Models, adversary type, fine-grained information, game theory, Games, graph theory, graphical coordination games, Human Behavior, Metrics, multi-agent systems, Network topology, optimal system design, Planning, pubcrawl, resilience, Resiliency, Scalability, security, security of data, security strategy, system operator, System performance, Topology, unknown adversary

How does information regarding an adversary's intentions affect optimal system design? This paper addresses this question in the context of graphical coordination games where an adversary can indirectly influence the behavior of agents by modifying their payoffs. We study a situation in which a system operator must select a graph topology in anticipation of the action of an unknown adversary. The designer can limit her worst-case losses by playing a security strategy, effectively planning for an adversary which intends maximum harm. However, fine-grained information regarding the adversary's intention may help the system operator to fine-tune the defenses and obtain better system performance. In a simple model of adversarial behavior, this paper asks how much a system operator can gain by fine-tuning a defense for known adversarial intent. We find that if the adversary is weak, a security strategy is approximately optimal for any adversary type; however, for moderately-strong adversaries, security strategies are far from optimal.

Citation Keycollins_exploiting_2020