(untitled) (Journal of The Colloquium for Information Systems Security Education, 2025)
As AI technology continues to advance, voice cloning is becoming increasingly easy. Recently, cases of fraud involving audio forgery using AI technology have emerged, making it particularly important to covertly embed information and verify the authenticity and integrity of audio. Digital Audio Water-marking has thus become a crucial tool in this context. This study proposes an improved Phase Coding audio steganography algorithm that dynamically segments the audio signal and embeds information into the phase components of the mid-frequency range. This approach not only enhances the algorithm’s resistance to steganalysis but also simplifies the computational process, ensuring the authenticity and integrity of audio both efficiently and securely.