A Framework for Investigating the Performance of Chaotic-Map Truly Random Number Generators

2012/11/06 by Ahmad Beirami, Beirami, Ahmad, Hamid Reza Nejati +1
Computer Science · #Cellular Automata and Applications #Chaos-based Image/Signal Encryption #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Neural Networks and Applications

paper · pdf · doi:10.48550/arxiv.1211.1234

openalex publication_date 2012/11/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper, we approximate the hidden Markov model of chaotic-map truly random number generators (TRNGs) and describe its fundamental limits based on the approximate entropy-rate of the underlying bit-generation process. We demonstrate that entropy-rate plays a key role in the performance and robustness of chaotic-map TRNGs, which must be taken into account in the circuit design optimization. We further derive optimality conditions for post-processing units that extract truly random bits from a raw-RNG.

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