Audio Attack

Audio attacks exploit vulnerabilities in audio processing systems, aiming to manipulate or deceive them through malicious audio modifications. Current research focuses on developing robust detection methods, often employing contrastive learning and advanced architectures like RawNet, and analyzing the effectiveness of various attack strategies, including noise injection and spectrum manipulation, against commercial voice control systems and automatic speech recognition. This field is crucial for enhancing the security of voice-controlled devices and AI systems that rely on audio input, impacting areas like cybersecurity, digital forensics, and the trustworthiness of AI-driven applications.