Abstract
Random number generators (RNGs) play an important role in many real-world applications. Besides true hardware RNGs, one important class are deterministic random number generators. Such generators do not possess the unpredictability of true RNGs, but still have a widespread usage. For a deterministic RNG to be used in cryptography, it needs to fulfill a number of conditions related to the speed, the security, and the ease of implementation. In this paper, we investigate how to evolve deterministic RNGs with Cartesian Genetic Programming. Our results show that such evolved generators easily pass all randomness tests and are extremely fast/small in hardware.
Author supplied keywords
Cite
CITATION STYLE
Picek, S., Sisejkovic, D., Rozic, V., Yang, B., Jakobovic, D., & Mentens, N. (2016). Evolving cryptographic pseudorandom number generators. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9921 LNCS, pp. 613–622). Springer Verlag. https://doi.org/10.1007/978-3-319-45823-6_57
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
