Resistance of orthogonal Gaussian fingerprints to collusion attacks
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Performance of detection statistics under collusion attacks on independent multimedia fingerprints
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Group-oriented fingerprinting for multimedia forensics
EURASIP Journal on Applied Signal Processing
Performance of orthogonal fingerprinting codes under worst-case noise
IEEE Transactions on Information Forensics and Security
Robust MC-CDMA-based fingerprinting against time-varying collusion attacks
IEEE Transactions on Information Forensics and Security
Anti-collusion fingerprinting for multimedia
IEEE Transactions on Signal Processing
Collusion-Resistant Video Fingerprinting for Large User Group
IEEE Transactions on Information Forensics and Security
Joint coding and embedding techniques for MultimediaFingerprinting
IEEE Transactions on Information Forensics and Security
Collusion-secure fingerprinting for digital data
IEEE Transactions on Information Theory
Image-adaptive watermarking using visual models
IEEE Journal on Selected Areas in Communications
Secure spread spectrum watermarking for multimedia
IEEE Transactions on Image Processing
Applying informed coding and embedding to design a robust high-capacity watermark
IEEE Transactions on Image Processing
Forensic analysis of nonlinear collusion attacks for multimedia fingerprinting
IEEE Transactions on Image Processing
Anti-collusion forensics of multimedia fingerprinting using orthogonal modulation
IEEE Transactions on Image Processing
A collusion attack optimization strategy for digital fingerprinting
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) - Special Issue on Multimedia Security
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Digital fingerprinting is a technology which aims to embed unique marks with traceability in order to identify users who use their multimedia content for unintended purpose. A cost-efficient attack against digital fingerprinting, known as collusion attack, involves a group of users who combine their fingerprinted content for the purpose of attenuating or removing the fingerprints. In this paper, we analyze and simulate the effect of Gaussian noise with different energies added in the noise-free forgery on both the detection performance of correlation-based detector and the perceptual quality of the attacked content. Based upon the analysis and the principal of informed watermark embedding, we propose a novel collusion attack strategy, self-adaptive noise optimization (SANO) collusion attack. The experimental results, under the assumption that orthogonal fingerprints are used, show that the proposed collusion attack performs more effectively than the most of existed collusion attacks. Less than three pieces of fingerprinted content can sufficiently interrupt orthogonal fingerprints which accommodate many thousands of users. Meanwhile, high fidelity of the attacked content is retained after the proposed collusion attack.