Illusion: Safeguarding Topology Confidentiality in LLM Multi-Agent Systems via Behavior-Preserving Obfuscation

Summary

The paper proposes Illusion, a proactive defense that conceals the communication topology of LLM multi-agent systems by injecting fake edges and fake messages. Low-impact candidates are chosen to preserve output-distribution equivalence and task accuracy. In experiments, edge-level F1 drops from over 0.87 to 0.62 and graph similarity from over 0.94 to 0.71, and the fake edges resist similarity-based and LLM-judge filtering, even under adaptive pruning.

Mitigation

The proposed mitigation is Illusion, a proactive topology obfuscation defense that injects fake edges and fake messages into LLM-MAS communication to present attackers with a deceptive topology.

Topics

• AI agents

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