CRYPTO '94 Proceedings of the 14th Annual International Cryptology Conference on Advances in Cryptology
Optimal probabilistic fingerprint codes
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
On the randomness complexity of efficient sampling
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
Optimal probabilistic fingerprint codes
Journal of the ACM (JACM)
Efficient Traitor Tracing from Collusion Secure Codes
ICITS '08 Proceedings of the 3rd international conference on Information Theoretic Security
An improvement of discrete Tardos fingerprinting codes
Designs, Codes and Cryptography
Efficient pseudorandom generators based on the DDH assumption
PKC'07 Proceedings of the 10th international conference on Practice and theory in public-key cryptography
Optimization of Tardos's fingerprinting codes in a viewpoint of memory amount
IH'07 Proceedings of the 9th international conference on Information hiding
On the security of pseudorandomized information-theoretically secure schemes
ICITS'09 Proceedings of the 4th international conference on Information theoretic security
A short random fingerprinting code against a small number of pirates
AAECC'06 Proceedings of the 16th international conference on Applied Algebra, Algebraic Algorithms and Error-Correcting Codes
Collusion-secure fingerprinting for digital data
IEEE Transactions on Information Theory
Hi-index | 0.00 |
Recently, the authors proposed an evaluation technique for pseudorandom generator-based randomness reduction of cryptographic schemes against computationally unbounded attack algorithms. In this article, we apply the technique to the case of fingerprint codes and verify the effectiveness. Then we propose a technique that improves the randomness reduction by dividing the target randomness into suitable parts and using a separate pseudorandom generator for each part. Considering fingerprint codes as a typical example, we give a theoretical evaluation of the proposed technique, and also a numerical evaluation showing that our technique improves the effect of randomness reduction to about 29 times as good as the plain randomness reduction in a reasonable setting.