A genetic strategy to design cellular automata based block ciphers

• A new dynamic and flexible construction of block ciphers is proposed using non uniform cellular automata.
• The proposed model enable the construction of a multidimensional space of cipher’s instances.
• The defined space is explored using genetic algorithms to find the optimal solution.
• The strict avalanche criterion is used as a fitness function.
• The obtained solution is benchmarked and shown to provide high security performances.

We propose an evolutionary computation approach to design a fast and secure block cipher using non-uniform second-order cellular automata. We build a flexible block ciphering model that permit the construction of a huge space of possible instances defined each one by a finite set of elementary transition rules. The constructed space is explored using a genetic algorithms strategy in order to find an optimal solution with respect to the strict avalanche criterion used as fitness measurements. The genetically designed cipher is benchmarked experimentally using conventional statistical tests, and shown to have very admissible characteristics leading to a very acceptable level of cryptographic security. Moreover, performances analysis shows that the designed cipher permit to achieve a high encryption/decryption speed, and compete many of the existing standardized ciphers.