38 research outputs found
Anti-Collusion Fingerprinting for Multimedia
Digital fingerprinting is a technique for identifyingusers who might try to use multimedia content for unintendedpurposes, such as redistribution. These fingerprints are typicallyembedded into the content using watermarking techniques that aredesigned to be robust to a variety of attacks. A cost-effectiveattack against such digital fingerprints is collusion, whereseveral differently marked copies of the same content are combinedto disrupt the underlying fingerprints. In this paper, weinvestigate the problem of designing fingerprints that canwithstand collusion and allow for the identification of colluders.We begin by introducing the collusion problem for additiveembedding. We then study the effect that averaging collusion hasupon orthogonal modulation. We introduce an efficient detectionalgorithm for identifying the fingerprints associated with Kcolluders that requires O(K log(n/K)) correlations for agroup of n users. We next develop a fingerprinting scheme basedupon code modulation that does not require as many basis signalsas orthogonal modulation. We propose a new class of codes, calledanti-collusion codes (ACC), which have the property that thecomposition of any subset of K or fewer codevectors is unique.Using this property, we can therefore identify groups of K orfewer colluders. We present a construction of binary-valued ACCunder the logical AND operation that uses the theory ofcombinatorial designs and is suitable for both the on-off keyingand antipodal form of binary code modulation. In order toaccommodate n users, our code construction requires onlyO(sqrt{n}) orthogonal signals for a given number of colluders.We introduce four different detection strategies that can be usedwith our ACC for identifying a suspect set of colluders. Wedemonstrate the performance of our ACC for fingerprintingmultimedia and identifying colluders through experiments usingGaussian signals and real images.This paper has been submitted to IEEE Transactions on Signal Processing</I
On the Implementation of Spread Spectrum Fingerprinting in Asymmetric Cryptographic Protocol
<p/> <p>Digital fingerprinting of multimedia contents involves the generation of a fingerprint, the embedding operation, and the realization of traceability from redistributed contents. Considering a buyer's right, the asymmetric property in the transaction between a buyer and a seller must be achieved using a cryptographic protocol. In the conventional schemes, the implementation of a watermarking algorithm into the cryptographic protocol is not deeply discussed. In this paper, we propose the method for implementing the spread spectrum watermarking technique in the fingerprinting protocol based on the homomorphic encryption scheme. We first develop a rounding operation which converts real values into integer and its compensation, and then explore the tradeoff between the robustness and communication overhead. Experimental results show that our system can simulate Cox's spread spectrum watermarking method into asymmetric fingerprinting protocol.</p
Fingerprinting with Minimum Distance Decoding
This work adopts an information theoretic framework for the design of
collusion-resistant coding/decoding schemes for digital fingerprinting. More
specifically, the minimum distance decision rule is used to identify 1 out of t
pirates. Achievable rates, under this detection rule, are characterized in two
distinct scenarios. First, we consider the averaging attack where a random
coding argument is used to show that the rate 1/2 is achievable with t=2
pirates. Our study is then extended to the general case of arbitrary
highlighting the underlying complexity-performance tradeoff. Overall, these
results establish the significant performance gains offered by minimum distance
decoding as compared to other approaches based on orthogonal codes and
correlation detectors. In the second scenario, we characterize the achievable
rates, with minimum distance decoding, under any collusion attack that
satisfies the marking assumption. For t=2 pirates, we show that the rate
is achievable using an ensemble of random linear
codes. For , the existence of a non-resolvable collusion attack, with
minimum distance decoding, for any non-zero rate is established. Inspired by
our theoretical analysis, we then construct coding/decoding schemes for
fingerprinting based on the celebrated Belief-Propagation framework. Using an
explicit repeat-accumulate code, we obtain a vanishingly small probability of
misidentification at rate 1/3 under averaging attack with t=2. For collusion
attacks which satisfy the marking assumption, we use a more sophisticated
accumulate repeat accumulate code to obtain a vanishingly small
misidentification probability at rate 1/9 with t=2. These results represent a
marked improvement over the best available designs in the literature.Comment: 26 pages, 6 figures, submitted to IEEE Transactions on Information
Forensics and Securit