Elements of information theory
Elements of information theory
Fundamentals of speech recognition
Fundamentals of speech recognition
A Perceptual Audio Hashing Algorithm: A Tool for Robust Audio Identification and Information Hiding
IHW '01 Proceedings of the 4th International Workshop on Information Hiding
Multipurpose Audio Watermarking
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
Convex Optimization
Rate-adaptive codes for distributed source coding
Signal Processing - Special section: Distributed source coding
Blind watermarking applied to image authentication
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
Watermarking-based digital audio data authentication
EURASIP Journal on Applied Signal Processing
Rate allocation for robust video streaming based on distributed video coding
Image Communication
Cocktail watermarking for digital image protection
IEEE Transactions on Multimedia
Hierarchical watermarking for secure image authentication with localization
IEEE Transactions on Image Processing
Distributed video coding: trends and perspectives
Journal on Image and Video Processing - Special issue on distributed video coding
Towards content-based audio fragment authentication
MM '11 Proceedings of the 19th ACM international conference on Multimedia
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The increasing development of peer-to-peer networks for delivering and sharing multimedia files poses the problem of how to protect these contents from unauthorized manipulations. In the past few years, a large amount of techniques have been proposed to identify whether a multimedia content has been illegally tampered or not. Nevertheless, very few efforts have been devoted to identifying which kind of attack has been carried out, especially due to the large data required for this task. We propose a novel hashing scheme which exploits the paradigms of compressive sensing and distributed source coding to generate a compact hash signature, and apply it to the case of audio content protection. The audio content provider produces a small hash signature by computing a limited number of random projections of a perceptual, time-frequency representation of the original audio stream; the audio hash is given by the syndrome bits of an LDPC code applied to the projections. At the content user side, the hash is decoded using distributed source coding tools. If the tampering is sparsifiable or compressible in some orthonormal basis or redundant dictionary, it is possible to identify the time-frequency position of the attack, with a hash size as small as 200 bits/second; the bit saving obtained by introducing distributed source coding ranges between 20% to 70%.