MysticMask: Adversarial Mask for Impersonation Attack Against Face Recognition Systems

In our increasingly interconnected digital world, face recognition serves as a vital security layer for identity verification. However, impersonation attacks pose a significant threat to face recognition systems. While adversarial attacks have proven effective in impersonation, current methods primarily target face recognition, overlooking other crucial processes in real-world applications, such as action-based liveness detection.To address this gap, we introduce MysticMask, a novel adversarial mask attack designed to penetrate the entire face recognition pipeline for impersonation. MysticMask operates in the 3D domain, leveraging foldable medical face masks that automatically align with facial landmarks, enabling accurate physical simulations. MysticMask attacks all processes in a face recognition system simultaneously, including face detection, action-based liveness detection, and face recognition. Additionally, a landmark alignment technique is proposed to pass action-based liveness detection. Extensive experiments conducted in both simulated 3D and real-world scenarios demonstrate MysticMask’s superiority over state-of-the-art methods.