Exploiting ergodicity of the logistic map using deep-zoom to improve security of chaos-based cryptosystems
This work addresses security issues in chaos-based cryptosystems for cryptography applications, but it is incremental as it builds on an existing cryptosystem.
The paper tackled the problem of improving security in chaos-based cryptosystems by exploiting the deep-zoom properties of the chaotic k-logistic map to enhance randomness and reduce predictability, resulting in a reliable method that eliminates weaknesses from a previous cryptosystem.
This paper explores the deep-zoom properties of the chaotic k-logistic map, in order to propose an improved chaos-based cryptosystem. This map was shown to enhance the random features of the Logistic map, while at the same time reducing the predictability about its orbits. We incorporate its strengths to security into a previously published cryptosystem to provide an optimal pseudo-random number generator (PRNG) as its core operation. The result is a reliable method that does not have the weaknesses previously reported about the original cryptosystem.