A simple unpredictable pseudo random number generator
SIAM Journal on Computing
The discrete log is very discreet
STOC '90 Proceedings of the twenty-second annual ACM symposium on Theory of computing
How to generate cryptographically strong sequences of pseudo random bits
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
Inferring a sequence generated by a linear congruence
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
Theory and application of trapdoor functions
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
Trapdoor pseudo-random number generators, with applications to protocol design
SFCS '83 Proceedings of the 24th Annual Symposium on Foundations of Computer Science
Unbiased bits from sources of weak randomness and probabilistic communication complexity
SFCS '85 Proceedings of the 26th Annual Symposium on Foundations of Computer Science
Independent Unbiased Coin Flips From A Correlated Biased Source: A Finite State Markov Chain
SFCS '84 Proceedings of the 25th Annual Symposium onFoundations of Computer Science, 1984
Generating Quasi-Random Sequences From Slightly-Random Sources
SFCS '84 Proceedings of the 25th Annual Symposium onFoundations of Computer Science, 1984
Hidden Number Problem with the Trace and Bit Security of XTR and LUC
CRYPTO '02 Proceedings of the 22nd Annual International Cryptology Conference on Advances in Cryptology
All Bits ax+b mod p are Hard (Extended Abstract)
CRYPTO '96 Proceedings of the 16th Annual International Cryptology Conference on Advances in Cryptology
The security of all RSA and discrete log bits
Journal of the ACM (JACM)
Uniform results in polynomial-time security
EUROCRYPT'92 Proceedings of the 11th annual international conference on Theory and application of cryptographic techniques
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The next bit test was shown by Yao to be a universal test for sources of unbiased independent bits. The aim of this paper is to provide a rigorous methodology of how to test other properties of sources whose output distribution is not necessarily uniform. We prove the surprising result that the natural extension of the next bit test, even in the simplest case of biased independent bits, is no longer universal: We construct a source of biased bits, whose bits are obviously dependent and yet none of these bits can be predicted with probability of success greater than the bias. To overcome this difficulty, we develop new universal tests for arbitrary models of (potentially imperfect) sources of randomness.