Security Against Impersonation Attacks in Distributed Systems
This addresses security vulnerabilities in distributed decision-making for systems like autonomous networks or cooperative robotics, though it appears incremental as it builds on existing game theory frameworks.
The paper tackles the problem of adversarial impersonation in distributed multi-agent systems, showing that an adversary posing as a friendly agent can locally influence agents and cascade effects to destabilize efficient Nash equilibria in graphical coordination games.
In a multi-agent system, transitioning from a centralized to a distributed decision-making strategy can introduce vulnerability to adversarial manipulation. We study the potential for adversarial manipulation in a class of graphical coordination games where the adversary can pose as a friendly agent in the game, thereby influencing the decision-making rules of a subset of agents. The adversary's influence can cascade throughout the system, indirectly influencing other agents' behavior and significantly impacting the emergent collective behavior. The main results in this paper focus on characterizing conditions under which the adversary's local influence can dramatically impact the emergent global behavior, e.g., destabilize efficient Nash equilibria.