Solving polynomial systems with noise over F2: Revisited

Solving polynomial systems with noise over F2 is a fundamental problem in computer science, especially in cryptanalysis. ISBS is a new method for solving this problem based on the idea of incrementally solving the noisy polynomial systems and backtracking all the possible noises, and it has better performance than other methods in solving some problems generated from cryptanalysis. In this paper, some further researches on ISBS are presented. The structure and size of the search tree of ISBS are theoretically analyzed. Then two major improvements, artificial noise-bound strategy and s-direction approach, are proposed. Based on these improvements, a modified ISBS algorithm is implemented, and the experiments of solving the Cold Boot key recovery problems of the block cipher Serpent with symmetric noise, show that this modified algorithm is more efficient than the original one.