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Evolving Cryptographic Pseudorandom Number Generators

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 9921)


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.


  • Random number generators
  • Pseudorandomness
  • Cryptography
  • Cartesian Genetic Programming
  • Statistical tests

This work has been supported in part by Croatian Science Foundation under the project IP-2014-09-4882. In addition, this work was supported in part by the Research Council KU Leuven (C16/15/058) and IOF project EDA-DSE (HB/13/020).

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Correspondence to Stjepan Picek .

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Picek, S., Sisejkovic, D., Rozic, V., Yang, B., Jakobovic, D., Mentens, N. (2016). Evolving Cryptographic Pseudorandom Number Generators. In: Handl, J., Hart, E., Lewis, P., López-Ibáñez, M., Ochoa, G., Paechter, B. (eds) Parallel Problem Solving from Nature – PPSN XIV. PPSN 2016. Lecture Notes in Computer Science(), vol 9921. Springer, Cham.

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