BadAction: Backdoor Attacks on Interactive Video Generation via Action-Guided Triggers

Summary

Researchers present the first systematic study of backdoor attacks against the interactivity of interactive video generation (IVG) models. Their method, BadAction, implants predefined motion patterns into action sequences so that triggered models produce frozen future frames that ignore later user actions, while benign inputs behave normally. The attack reaches average success rates of 91.0% with action-only triggers and 80.4% with multimodal triggers, and it bypasses existing backdoor detection methods.

Topics

• Adversarial machine learning

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