Electronics · 2020 · 42 citations · 36 references
ComputingComputer ScienceComputer SecurityCryptographyDynamical SystemsChaos TheoryCryptographic AlgorithmsRandom Number GenerationCryptographic Random Number GenerationCryptographically Secure Pseudo-random Number GeneratorsLogistic MapPseudo-random Number GenerationPseudo-random Number GeneratorsPseudorandom GeneratorsRandomness GenerationSecure Random Number Generation
Robust chaotic systems, due to their inherent properties of mixing, ergodicity, and larger chaotic parameter space, constitute a perfect candidate for cryptography. This paper reports a novel method to generate random numbers using modified robust logistic map (MRLM). The non-smooth probability distribution function of robust logistic map (RLM) trajectories gives an un-even binary distribution in randomness test. To overcome this disadvantage in RLM, control of chaos (CoC) is proposed for smooth probability distribution function of RLM. For testing the proposed design, cryptographic random numbers generated by MRLM were vetted with National Institute of Standards and Technology statistical test suite (NIST 800-22). The results showed that proposed MRLM generates cryptographically secure random numbers (CSPRNG).
36
Communication Theory of Secrecy Systems*
Claude E. Shannon · Bell System Technical Journal · 1949 · 9.3K citations
Biogeography-Based Optimization
D. Simon · IEEE Transactions on Evolutionary Computation · 2008 · 4.3K citations
A NEW CHAOTIC ATTRACTOR COINED
Jinhu Lü, Guanrong Chen · International Journal of Bifurcation and Chaos · 2002 · 1.8K citations
Image encryption using chaotic logistic map
N.K. Pareek, Vinod Patidar, K. K. Sud · Image and Vision Computing · 2006 · 1.2K citations