When Critics Disagree: Adaptive Reward Poisoning Attacks in RIS-Aided Wireless Control System
Researchers have identified a novel attack vector against reinforcement learning systems in wireless networks by exploiting disagreement between dual critic networks in Soft Actor-Critic agents. The Disagreement-Guided Reward Poisoning attack targets high-uncertainty decision points where the two critics diverge, corrupting reward signals to push learned policies toward suboptimal behavior. This work exposes a structural vulnerability in a widely-used RL architecture when deployed in safety-critical control domains like spectrum management and RIS-assisted communications, raising questions about the robustness of actor-critic methods in adversarial wireless environments.
Modelwire context
ExplainerThe paper's key contribution isn't just that SAC agents can be attacked, but that attackers can systematically identify which decisions to poison by watching where the two critic networks disagree. This disagreement-guided targeting makes the attack far more efficient than random reward corruption.
This connects to the contextual bandit work from the same day, which showed that adaptive sampling strategies outperform passive approaches. Here, the attacker is doing something similar: adaptively choosing high-uncertainty points rather than poisoning uniformly. Both papers highlight how uncertainty and disagreement create exploitable structure in learning systems. The difference is intent: one paper optimizes for better learning, this one weaponizes the same principle against it.
If follow-up work demonstrates that adding a third critic or using ensemble disagreement thresholds actually prevents this attack in simulation, that validates the diagnosis. If instead attackers can still succeed with minimal overhead against hardened variants, the vulnerability runs deeper than the architecture choice.
Coverage we drew on
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MentionsSoft Actor-Critic · Reconfigurable Intelligent Surfaces · Cognitive Radio Network · Disagreement-Guided Reward Poisoning
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