Designing Stream Cipher Systems Using Genetic Programming

Abstract

AbstractGenetic programming is a good technique for finding near-global optimal solutions for complex problems, by finding the program used to solve the problems. One of these complex problems is designing stream cipher systems automatically. Steam cipher is an important encryption technique used to protect private information from an unauthorized access, and it plays an important role in the communication and storage systems. In this work, we propose a new approach for designing stream cipher systems of good properties, such as high degree of security and efficiency. The proposed approach is based on the genetic programming. Three algorithms are presented here, which are simple genetic programming, simulated annealing programming, and adaptive genetic programming. Experiments were performed to study the effectiveness of these algorithms in solving the underlying problem.KeywordsGenetic AlgorithmGenetic ProgrammingBoolean FunctionCellular AutomatonLinear ComplexityThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.