Pseudo-zernike moments-based audio content authentication algorithm robust against feature-analysed substitution attack
Content-based audio content authentication algorithms provide a method to solve the veracity and integrity of audio content. On the basic of pseudo-Zernike moments, an audio content authentication algorithm robust against feature-analysed substitution attack is proposed, which is aimed at some insecure issues in the existing content-based audio content authentication schemes. Firstly, the audio signal is cut into non-overlapping frames and each frame is divided into two segments, and each segment is scrambled. Then, synchronization codes generated by pseudo random sequence and watermark bits generated by pseudo-Zernike moments are embedded in the first and second segment, respectively, which are completed by quantizing the modulus of pseudo-Zernike moments. The scrambled segments used to generate and extract watermark are unknown to attackers. So, it is difficult for attackers to get the watermark generated and extracted to perform feature-analysed substitution attack. The synchronization code and watermark embedding method proposed is inaudible and has excellent ability to tolerance against common signal processing operations. Compared with the existing audio watermark algorithms based on pseudo-Zernike moments, the algorithm increases the embedding capacity and improves the security of the watermarking system.
pseudo-zernike moments audio content authentication synchronization code tamper localization