Applying PSO based technique for analysis of geffe generator cryptosystem

Abstract

The nature-inspired computational field is now being popularized as computational swarm intelligence. Computational swarm intelligence has been applied to solve many practical and complex optimization problems. The past decade has witnessed a lot of interest in applying computational swarm techniques for solving crypto problems. In this technical paper, binary particle swarm optimization (BPSO) based technique is applied to solve encrypted text messages enciphered with nonlinear pseudorandom key sequence of Geffe generator. The Geffe generator is a nonlinear binary key sequence generator. It consists of nonlinear combiner function and three linear feedback shift registers (LFSRs). Authors attempt to find initial states of all three shift registers of Geffe generator using divide-and-conquer approach and BPSO technique to reduce number of exhaustive search significantly. According to obtained results, correct initial bits of LFSRs can be computed to solve Geffe (11, 13, 31) crypts of length 400 characters by tuning BPSO parameters.