AI Research
OpenEvoShield: Dual Non-Stationary Continual Defense for Open-World Multi-Agent System Attacks
LLM-based multi-agent systems (LLM-MAS) are increasingly deployed in safety-critical applications, where adversaries inject malicious instructions through inter-agent communication to propagate harmful behaviors. Unlike static threats, these attacks are doubly dynamic: adversarie...
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ArXiv CS.AI
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ArXiv CS.AI
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This research addresses the critical challenge of dynamic, evolving attacks in multi-agent AI systems, crucial for securing safety-critical applications. OpenEvoShield's novel co-evolutionary defense framework offers a robust solution to detect and adapt to novel threats without sacrificing performance.
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