The optimal key estimation of stream ciphers and its approximation algorithm based on a probabilistic inference

A stream cipher is an important class of encryption algorithms. Its safety depends on the structure of the pseudorandom number generator used. There are various types of pseudo-random number generators in existence, and attack algorithms used on them have been studied individually. In this paper, we express the problem of attacks on a general stream cipher as a probabilistic inference problem, and formulate the optimal key estimation. We also propose a unified framework of attack algorithms that can be applied to a wide variety of stream ciphers. The optimal key estimation, however, has computational complexity. To reduce the complexity, an approximation algorithm based on a probabilistic inference is proposed. We also describe some attack algorithms used on practical pseudorandom number generators. Finally, the proposed algorithm is evaluated by through a computer simulation.