Perceptual Rubost Audio Hashing with Discrete Cosine Transformation
Paper ID : 1476-IST
1Mahdi Nouri *, 2Nooshin Farhangian
1Michigan University of Technology
2Islamic Azad University of Yadergar-e-Imam Khomeini
Perceptual hash functions provide a tool for fast and reliable identification of content. Robust hashing for multimedia authentication is an emerging research area. A novel key-dependent robust speech hashing based on speech production model is proposed in this article. The proposed hash functions are based on the periodicity series of the fundamental frequency. Robust hash is calculated based on linear spectrum frequencies (LSFs) which model the vocal tract. The correlation between LSFs is decoupled by discrete cosine transformation (DCT). A randomization scheme controlled by a secret key is applied in hash generation for random feature selection. The hash function is key-dependent and collision resistant. Meanwhile, it is highly robust to content preserving operations as well as having high accuracy of tampering localization. They are found, on one hand, to perform very satisfactorily in identification and verification tests, and on the other hand, to be very resilient to a large variety of attacks. Moreover, we address the issue of security of hashes and propose a keying technique, and thereby a key-dependent hash function.
DCT; Epicycloid Graph; Robust hashing; Linear spectrum frequencies