Signal Processing with Lapped Transforms
Signal Processing with Lapped Transforms
A modulated complex lapped transform and its applications to audio processing
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03
A Review of Audio Fingerprinting
Journal of VLSI Signal Processing Systems
From digital audiobook to secure digital multimedia-book
Computers in Entertainment (CIE) - Theoretical and Practical Computer Applications in Entertainment
Perceptual audio hashing functions
EURASIP Journal on Applied Signal Processing
Histogram-based image hashing scheme robust against geometric deformations
Proceedings of the 9th workshop on Multimedia & security
Markov modelling of fingerprinting systems for collision analysis
EURASIP Journal on Information Security
Journal on Image and Video Processing - Special issue on distributed video coding
Fragility analysis of adaptive quantization-based image hashing
IEEE Transactions on Information Forensics and Security
On detection with partial information in the Gaussian setup
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
A reversible acoustic steganography for integrity verification
IWDW'10 Proceedings of the 9th international conference on Digital watermarking
Random Gray code and its performance analysis for image hashing
Signal Processing
Histogram-based image hashing for searching content-preserving copies
Transactions on data hiding and multimedia security VI
Information Sciences: an International Journal
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Assuming that watermarking is feasible (say, against a limited set of attacks of significant interest), current methods use a secret key to generate and embed a watermark. However, if the same key is used to watermark different items, then each instance may leak partial information and it is possible that one may extract the whole secret from a collection of watermarked items. Thus it will be ideal to derive content dependent keys, using a perceptual hashing algorithm (with its own secret key) that is resistant to small changes and otherwise having randomness and unpredictability properties analogous to cryptographic MACs.The techniques here are also useful for synchronizing in streams to find fixed locations against insertion and deletion attacks. Say, one may watermark a frame in a stream and can synchronize oneself to that frame using keyed perceptual hash and a known value for that frame. Our techniques can be used for identification of audio clips as well as database lookups in a way resistant to formatting and compression. We propose a novel audio hashing algorithm to be used for audio watermarking applications, that uses signal processing and traditional algorithmic analysis (against an adversary).