GCP: Guarded Collaborative Perception With Spatial-Temporal Aware Malicious Agent Detection

Summary

The paper reveals a blind area confusion (BAC) attack that compromises existing single-shot outlier-based detection methods for collaborative perception in autonomous driving, where malicious agents send adversarial messages. It proposes GCP, a Guarded Collaborative Perception framework that combines a confidence-scaled spatial concordance loss with temporal reconstruction of historical bird's eye view motion flows, joined by a spatial-temporal Benjamini-Hochberg test. Experiments report up to 34.69% AP@0.5 improvement over state-of-the-art CP defenses under BAC attacks, and 5-8% under other typical attacks.

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