Replay Attack

Replay attacks, where recorded audio or video is used to impersonate a genuine user, pose a significant threat to various authentication systems, including speaker verification and face recognition. Current research focuses on developing robust detection methods, employing techniques like graph Fourier transforms for audio analysis, deep learning models (including convolutional neural networks and recurrent neural networks) for feature extraction and classification, and adversarial attack strategies to evaluate system vulnerabilities. These advancements are crucial for enhancing the security of biometric authentication and other applications susceptible to replay attacks, impacting both the scientific understanding of security vulnerabilities and the development of more secure technologies.