The proposed multi-layered backdoor detection system was evaluated across 10 diverse scenarios, including benign tasks, keyword-triggered attacks, semantic backdoors, and distributed multi-agent attacks. In the simulation experiments, Total Scenarios: 10 | Attack Scenarios: 5 | Benign Scenarios: 5, are prepared and Detection Mechanisms: 5 | Agent Architecture: 3-agent pipeline with a dedicated auditor are also prepared as the proposed system. All experiments executed successfully with comprehensive logging and tracing enabled. The system achieved perfect detection with zero false positives. The simulation experiments validate the effectiveness of the multi-layered defense architecture for detecting distributed backdoors in multi-agent LLM systems. These results demonstrate that architectural security approaches—treating multi-agent systems as distributed computing environments with Byzantine fault tolerance—can provide robust protection against sophisticated backdoor attacks without requiring model-level guarantees or training data access.
Kohei Arai (Thu,) studied this question.