Resistance of orthogonal Gaussian fingerprints to collusion attacks
Digital fingerprinting is a means to offer protection to digital data by which fingerprints embedded in the multimedia are capable of identifying unauthorized use of digital content. A powerful attack that can be employed to reduce this tracing capability is collusion. We study the collusion resistance of a fingerprinting system employing Gaussian distributed fingerprints and orthogonal modulation. We propose a likelihood-based approach to estimate the number of colluders, and introduce the thresholding detector for colluder identification. We first analyze the collusion resistance of a system to the average attack by considering the probability of a false negative and the probability of a false positive when identifying colluders. Lower and upper bounds for the maximum number of colluders are derived. We then show that the detectors are robust to different attacks. We further study different sets of performance criteria.