Resistance of digital watermarks to collusive attacks

Kilian, Joe; Leighton, Frank Thomson; Matheson, Lesley R.; Shamoon, T.; Tarjan, Robert E.; Zane, Francis

doi:10.1109/isit.1998.708876

Cited by 61 publications

(102 citation statements)

References 8 publications

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“…The Gaussian assumption is motivated by the Central Limit Theorem (CLT): A user accusation consists of a sum of per-segment contributions, which are independent and identically distributed 1 The proportionality m ∝ c 2 0 was already known in the context of spread-spectrum watermarking. Kilian et al [9] showed that, if the watermarks have a component-wise normal distribution, then Ω( p m/ln n) differently marked copies are required to successfully erase any mark with non-negligible probability.…”

Section: Exact Computation Of the False Positive Error Probabilitymentioning

confidence: 99%

False positive probabilities in q-ary Tardos codes: comparison of attacks

Simone

Škorić

2014

Des. Codes Cryptogr.

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We investigate False Positive (FP) accusation probabilities for q-ary Tardos codes in the Restricted Digit Model. We employ a computation method recently introduced by us, to which we refer as Convolution and Series Expansion (CSE). We present a comparison of several collusion attacks on q-ary codes: majority voting, minority voting, Interleaving,μ-minimizing and Random Symbol (the q-ary equivalent of the Coin Flip strategy). The comparison is made by looking at the FP rate at approximately fixed False Negative rate. In nearly all cases we find that the strongest attack is either minority voting orμ-minimizing, depending on the exact setting of parameters such as alphabet size, code length, and coalition size.Furthermore, we present results on the convergence speed of the CSE method, and we show how FP rate computations for the Random Symbol strategy can be sped up by a precomputation step.

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Section: Exact Computation Of the False Positive Error Probabilitymentioning

confidence: 99%

False positive probabilities in q-ary Tardos codes: comparison of attacks

Simone

Škorić

2014

Des. Codes Cryptogr.

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“…Schemes based on perceptual modeling that attempt to insert maximumpower watermarks are much harder to attack, but small amounts of scaling and cropping will erase many kinds of watermarks. For example, Kilian, et al [17] observed that the CKLS mark can be rendered unreadable by cropping a few rows and columns of pixels and scaling the image to the original size. Such an attack can be countered by aligning (or registering) to the original image; or, if the original is not available, by aligning to a previously inserted registration mark, or by using a watermark that is robust to such transformations, as discussed in Section 5.…”

Section: Robustnessmentioning

confidence: 99%

“…Kilian, et al [17] have observed that correlative-reader watermarks that use a componentwise {-1, 1} or {0, 1} distribution (common in the literature) or even a component-wise uniform distribution are at risk of attack with as few as five or six differently-marked copies. Resistance to collusive attack is the main focus of the theoretical work we discuss in the next section.…”

Section: Robustnessmentioning

confidence: 99%

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Robustness and security of digital watermarks

Matheson

Mitchell

Shamoon

et al. 1998

Financial Cryptography

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Abstract. Digital watermarking is a nascent but promising technology that offers protection of unencrypted digital content. This paper is a brief technical survey of the multimedia watermarking landscape. The three main technical challenges faced by watermarking algorithms are fidelity, robustness and security. Current watermarking methods offer possibly acceptable fidelity and robustness against certain types of processing, such as data compression and noise addition, but are not sufficiently robust against geometric transforms such as scaling and cropping of images. Theoretical approaches have been developed that could lead to secure watermarking methods, but substantial gaps remain between theory and practice.

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“…Our problem is different, however, from the collusion-secure fingerprint problem [2,9,12] in the way the watermarked sequences (queries) are generated. In the collusion-attack setting, each user is assigned a unique fingerprint, and an object watermarked with the unique fingerprint is distributed to each user.…”

Section: Introductionmentioning

confidence: 99%

Security of Public Watermarking Schemes for Binary Sequences

Chang

2002

Information Hiding

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Abstract. In this paper, we focus on the security aspect of public watermarking schemes. Specifically, given a watermarked sequence I, we consider smart attackers whose task is to find a non-watermarked sequence I using as few calls to the publicly available detection routine as possible. We restrict the media to binary sequences and use Hamming distance as the measure. We study a class of watermarking schemes and give an attacker who uses expected O(d(1 + log(n/k))) calls to find such I , where d and k are determined by the false alarm and distortion of the scheme, and n is the length of the sequence. This attacker is optimal when k = o(n). By taking the number of calls required as a measure of the security, we can trade-off the requirements on security, false alarm and distortion.

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Resistance of digital watermarks to collusive attacks

Cited by 61 publications

References 8 publications

False positive probabilities in q-ary Tardos codes: comparison of attacks

False positive probabilities in q-ary Tardos codes: comparison of attacks

Robustness and security of digital watermarks

Security of Public Watermarking Schemes for Binary Sequences

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