Dimensions overall score 7.0

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• DiPA enables rapid deployment of adversarial attacks by displaying patches on smartphone screens instead of printing them.method 95%
• DiPA achieves a higher attack success rate (ASR) against a real-world FR camera compared to existing physical attack methods.result 90%
• DiPA maintains higher mean confidence of face presence during attacks compared to other methods, ensuring the face-detection module is not disrupted.result 90%
• DiPA uses an ensemble of state-of-the-art face-recognition models (ArcFace, MagFace, CosFace) to enhance transferability to unseen commercial systems.technical 85%
• DiPA represents a novel attack modality for pervasive environments where mobile devices continuously interact with sensing infrastructures.technical 85%
• The demonstration shows DiPA can perform real-time dodging attacks against a deployed face-recognition camera.result 80%
• DiPA reveals critical vulnerabilities at the intersection of mobile devices, pervasive vision, and sensor-driven authentication infrastructures.limitation 75%
• The method does not test proprietary defenses, indicating a potential limitation in scope.limitation 70%

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