4.6 Article

An Improved Absolute-Cosine Chaotification Model and Its Simple Application in PRNG

期刊

IEEE ACCESS
卷 11, 期 -, 页码 59346-59356

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2023.3282370

关键词

~Chaos; chaotic behavior; 2D-ACCM; field-programmable gate array (FPGA); pseudo-random number generator (PRNG)

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This paper proposes a new two-dimensional absolute-cosine chaotic model (ACCM) that can generate chaotic maps with simple structures and complex behaviors based on existing chaotic systems. Experimental results show the effectiveness of the model and its applications in hardware implementation and pseudo-random number generation.
Chaotic systems are widely used in various aspects such as information security, signal processing, and synchronous control. The structural complexity and the chaotic behavior of chaotic systems are two significant factors affecting their practical applications. In this paper, we propose a universal two-dimensional (2D) absolute-cosine chaotic model (ACCM). The 2D-ACCM is composed of a nonlinear bounded cosine function and an absolute value function. It can construct new chaotic maps with simple structures and complex chaotic behaviors on the basis of existing chaotic systems. To verify the effectiveness of the proposed system, we first choose two existing one-dimensional (1D) chaotic maps and one existing 2D chaotic map as the seed maps of the 2D-ACCM to generate two new maps, respectively. The results of chaotic behavior analysis show that these two new maps have more complex chaotic behavior and wider chaotic ranges than seed maps and some advanced chaotic maps. Then a hardware experiment platform based on a field-programmable gate array (FPGA) is used for the hardware implementation of the new maps. Finally, a simple chaos-based pseudo-random number generator (PRNG) is introduced to show the practical application. The experimental results show that the new maps can be easily implemented on the FPGA and the chaos-PRNGs can generate pseudo-random numbers with excellent randomness.

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