Anti-collusion fingerprinting for multimedia

Abstract

Digital fingerprinting is a technique for identifying users who might try to use multimedia content for unintended purposes, such as redistribution. These fingerprints are typically embedded into the content using watermarking techniques that are designed to be robust to a variety of attacks. A cost-effective attack against such digital fingerprints is collusion, where several differently marked copies of the same content are combined to disrupt the underlying fingerprints. In this paper, we investigate the problem of designing fingerprints that can withstand collusion and allow for the identification of colluders. We begin by introducing the collusion problem for additive embedding. We then study the effect that averaging collusion has upon orthogonal modulation. We introduce an efficient detection algorithm for identifying the fingerprints associated with K colluders that requires O(K log(n/K)) correlations for a group of n users. We next develop a fingerprinting scheme based upon code modulation that does not require as many basis signals as orthogonal modulation. We propose a new class of codes, called anti-collusion codes (ACC), which have the property that the composition of any subset of K or fewer codevectors is unique. Using this property, we can therefore identify groups of K or fewer colluders. We present a construction of binary-valued ACC under the logical AND operation that uses the theory of combinatorial designs and is suitable for both the on-off keying and antipodal form of binary code modulation. In order to accommodate n users, our code construction requires only O(√ n) orthogonal signals for a given number of colluders. We introduce four different detection strategies that can be used with our ACC for identifying a suspect set of colluders. We demonstrate the performance of our ACC for fingerprinting multimedia and identifying colluders through experiments using Gaussian signals and real images.

Improving Collusion Resistance of Error Correcting Code Based Multimedia Fingerprinting

“…1(a)(c) a huge gap on the collusion resistance between the two systems. For orthogonal fingerprinting, the probability of colluder detection under interleaving collusion is comparable to that under averaging collusion owing to the orthogonal spreading [6]. On the other hand, the detection probability of the ECC fingerprinting drops sharply when more than five colluders come to create an interleaved copy, even when WNR is high.…”

“…The other type is the averaging collusion, whereby colluders average the corresponding components in their copies to generate a colluded version. Additional distortion may be added to the multimedia signal, which is typically modelled as an additive noise [6].…”

“…A qary ECC code resisting c colluders, constructed as the c-traceability code or c-TA code in short, was employed and extended to deal with symbol erasures contributed by noise or cropping in multimedia signal domain [5]. A recent code based on combinatorial design was proposed in [6], where each code bit is embedded in an overlapped fashion by modulating a spreading sequence that Contact information: {shanhe, minwu}@eng.umd.edu covers the entire multimedia signal. The overlap spreading confines the types of manipulation from colluders, and colluders can be identified through the code bits shared by them.…”

“…We have observed that the existing ECC fingerprinting works put most of the attention on the code layer and few work has considered the interaction between coding and embedding. In the mean time, joint consideration of coding and embedding has shown promising results recently in [6] for non-segment based fingerprinting. This motivates us to examine the interplay between the ECC code layer and the embedding layer.…”

An Adaptive Scalable Watermark Scheme for High-Quality Audio Archiving and Streaming Applications

“…If an unauthorized user intercepts the bitstream somewhere before the transcoding server and attempt to recover the lossless audio, he will fail since he can only generate the watermarked low-quality audio. In addition, when the watermark embeds anti-collusion fingerprint [13], the preserved watermark will help to trace the source of the interception.…”