Regular simplex fingerprints and their optimality properties

Authors:
Negar Kiyavash;Pierre Moulin;Ton Kalker
Affiliations:
Coordinated Science Laboratory, Department of Industrial and Enterprise Systems Engineering, University of Illinois at Urbana-Champaign, Urbana, IL;Beckman Institute, the Coordinated Science Laboratory, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL;Hewlett Packard Laboratories, Multimedia Communication and Networking Department, Palo Alto, CA
Venue:
IEEE Transactions on Information Forensics and Security
Year:
2009

Citing 5
Cited 3

Collusion-Secure Fingerprinting for Digital Data (Extended Abstract)

CRYPTO '95 Proceedings of the 15th Annual International Cryptology Conference on Advances in Cryptology
Optimal Gaussian fingeprint decoders

ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Performance of orthogonal fingerprinting codes under worst-case noise

IEEE Transactions on Information Forensics and Security
A note on the limits of collusion-resistant watermarks

EUROCRYPT'99 Proceedings of the 17th international conference on Theory and application of cryptographic techniques
Anti-collusion forensics of multimedia fingerprinting using orthogonal modulation

IEEE Transactions on Image Processing

Performance of orthogonal fingerprinting codes under worst-case noise

IEEE Transactions on Information Forensics and Security
A detection theoretic approach to digital fingerprinting with focused receivers under uniform linear averaging Gaussian attacks

IEEE Transactions on Information Forensics and Security
A simple tracing algorithm for binary fingerprinting code under averaging attack

Proceedings of the first ACM workshop on Information hiding and multimedia security

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper addresses the design of additive fingerprints that are maximally resilient against linear collusion attacks on a focused correlation detector, as defined below. Let N be the length of the host vector and M ≤ N + 1 the number of users. The focused detector performs a correlation test in order to decide whether a user of interest is among the colluders. Both the fingerprint embedder and the colluders are subject to squared-error distortion constraints. We show that simplex fingerprints maximize a geometric figure of merit for this detector. In that sense they outperform orthogonal fingerprints but the advantage vanishes as M → ∞. They are also optimal in terms of minimizing the probability of error of the focused detector when the attack is a uniform averaging of the marked copies followed by the addition of white Gaussian noise. Reliable detection is guaranteed provided that the number of colluders K ≪ √N. Moreover, we study the probability of error performance of simplex fingerprints for the focused correlation detector when the colluders use nonuniform averaging plus white Gaussian noise attacks.