Error- and Collusion-Secure Fingerprinting for Digital Data
IH '99 Proceedings of the Third International Workshop on Information Hiding
Collusion Secure q-ary Fingerprinting for Perceptual Content
DRM '01 Revised Papers from the ACM CCS-8 Workshop on Security and Privacy in Digital Rights Management
Optimal probabilistic fingerprint codes
Journal of the ACM (JACM)
On the Design and Optimization of Tardos Probabilistic Fingerprinting Codes
Information Hiding
An improvement of discrete Tardos fingerprinting codes
Designs, Codes and Cryptography
Collusion-secure fingerprinting for digital data
IEEE Transactions on Information Theory
Tardos Fingerprinting is Better Than We Thought
IEEE Transactions on Information Theory
Experimental assessment of probabilistic fingerprinting codes over AWGN channel
IWSEC'10 Proceedings of the 5th international conference on Advances in information and computer security
A new soft decision tracing algorithm for binary fingerprinting codes
IWSEC'11 Proceedings of the 6th International conference on Advances in information and computer security
Asymptotic fingerprinting capacity in the combined digit model
IH'12 Proceedings of the 14th international conference on Information Hiding
Bias equalizer for binary probabilistic fingerprinting codes
IH'12 Proceedings of the 14th international conference on Information Hiding
A simple tracing algorithm for binary fingerprinting code under averaging attack
Proceedings of the first ACM workshop on Information hiding and multimedia security
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Binary fingerprinting codes with a length of theoretically minimum order were proposed by Tardos, and the traceability has been estimated under the well-known marking assumption. In this paper, we estimate the traceability and the false-positive probability of the fingerprinting code over AWGN channel, and propose a new accusation algorithm to catch more colluders with less innocent users. The design of our algorithm is based on the symmetric accusation algorithm proposed by Škoric et al. that focuses on the characteristic of the p.d.f. of the correlation scores. The proposed algorithm first estimates the strength of noise added to the code, and then calculates the specific correlation scores among candidate codewords using the characteristic of the noisy channel. The scores are finally classified into guilty and innocent by the threshold obtained from the p.d.f. The performance of the proposed tracing algorithm is evaluated by Monte Carlo simulation.