The Boneh–Shaw Fingerprinting Scheme is Better Than We Thought

Schaathun, Hans Georg

doi:10.1109/tifs.2006.873596

Cited by 22 publications

(18 citation statements)

References 17 publications

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“…In [18], we proved that by viewing the outer code as an error-correcting code, we can improve the error bound significantly, without changing the FP scheme. A second step was made in [21], where a new modified scheme was developed, using soft decision decoding for the BS inner code.…”

Section: The Boneh-shaw Codementioning

confidence: 98%

“…Codes for the Guth-Pfitzmann Marking Assumption were developed in [9,15,27], and all of these were based on the Boneh-Shaw code. Recently, we have seen [20] that the Boneh-Shaw code is theoretically more secure than originally assumed for the Boneh-Shaw Marking Assumption. In [22] we saw that the code can be further improved by using soft decision decoding.…”

Section: Introductionmentioning

confidence: 95%

“…Efficient known solutions for the top layer require huge alphabets. The inner FP code need not be very strong if the outer code can correct many errors [18]. Decoding in the inner layer can also be allowed to be relatively costly, because the code is relatively small.…”

Section: The Three-layer Modelmentioning

confidence: 99%

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On error-correcting fingerprinting codes for use with watermarking

Schaathun

2007

Multimedia Systems

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Digital fingerprinting has been suggested for copyright protection. Using a watermarking scheme, a fingerprint identifying the buyer is embedded in every copy sold. If an illegal copy appears, it can be traced back to the guilty user. By using collusion-secure codes, the fingerprinting system is made secure against cut-and-paste attacks. In this paper we study the interface between the collusion-secure fingerprinting codes and the underlying watermarking scheme, and we construct several codes which are both error-correcting and collusion-secure. Error-correction makes the system robust against successful attacks on the watermarking layer.

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Section: The Boneh-shaw Codementioning

confidence: 98%

Section: Introductionmentioning

confidence: 95%

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On error-correcting fingerprinting codes for use with watermarking

Schaathun

2007

Multimedia Systems

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“…Guth and Pfitzman [3] presented an adapted version of the Boneh-Shaw scheme for this new Marking Assumption. Our solution in this paper will be more efficient than that, by incorporating the latest improvements on Boneh-Shaw [4,5].…”

Section: Definition 2 (Guth-pfitzmann)mentioning

confidence: 99%

“…Once this was realised, it was evident that that we could improve the rate by using a weaker FP code and let the EC code compensate for that [4].…”

Section: Proceedings Of Thementioning

confidence: 99%

On Watermarking/Fingerprinting for Copyright Protection

Schaathun¹

First International Conference on Innovative Computing, Information and Control - Volume I (ICICIC'06)

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Digital fingerprinting has been suggested for copyright protection. Using a watermarking scheme, a fingerprint identifying the buyer is embedded in every copy sold. If an illegal copy appears, it can be traced back to the guilty user. By using collusion-secure codes, the fingerprinting system is made secure against cut-and-paste attacks.In this paper we study the interface between the collusion-secure fingerprinting codes and the underlying watermarking scheme, and we construct several codes which are both error-correcting and collusion-secure. Error-correction makes the system robust against successful attacks on the watermarking layer.

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SVM‐based anti‐forensic method for spread‐spectrum fingerprinting

Feng

Ling

Zou

et al. 2012

Security Comm Networks

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Digital fingerprinting is an emerging digital forensic technology that has been developed to detect digital forgeries and identify the pirates who leak the copies. Understanding the weaknesses and limitations of existing fingerprinting schemes and designing anti-forensic approaches play an important role in the development of digital fingerprinting. In this paper, we propose a support vector machine (SVM)-based anti-forensic method capable of removing the fingerprints from the previously marked images for spread-spectrum fingerprinting. We first estimate the parameters of the embedded fingerprint superposed on the frequency coefficients of the original signal. Then, we select the best basis through wavelet packet decomposition for thresholding the fingerprinted coefficients. Furthermore, an SVM-based classifier is used to measure the existence of the pirates' fingerprints. The experimental results show that the proposed method is more effective than the other examined approaches. About three pieces of fingerprinted content are able to interrupt the fingerprinting system that accommodates thousands of users. Meanwhile, high fidelity of the attacked content is retained.

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The Boneh–Shaw Fingerprinting Scheme is Better Than We Thought

Cited by 22 publications

References 17 publications

On error-correcting fingerprinting codes for use with watermarking

On error-correcting fingerprinting codes for use with watermarking

On Watermarking/Fingerprinting for Copyright Protection

SVM‐based anti‐forensic method for spread‐spectrum fingerprinting

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