Open Access

ARTICLE

VLSI Implementation of Optimized 2D SIMM Chaotic Map for Image Encryption

M. Sundar Prakash Balaji^1,*, V. R. Vijaykumar², Kamalraj Subramaniam³, M. Kannan⁴, V. Ayyem Pillai⁵

1 Department of Electronics and Communication Engineering, RVS College of Engineering and Technology, Coimbatore, 641402, India
2 Department of Electronics and Communication Engineering, Anna University Regional Campus, Coimbatore, 641046, India
3 Department of Biomedical Engineering, Karpagam Academy of Higher Education, Coimbatore, 641021, India
4 Department of Electronics, MIT Campus, Chennai, 600044, India
5 Department of Electronics and Communication Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, 500090, India

* Corresponding Author: M. Sundar Prakash Balaji. Email:

Intelligent Automation & Soft Computing 2023, 35(3), 3155-3168. https://doi.org/10.32604/iasc.2023.028969

Received 22 February 2022; Accepted 29 March 2022; Issue published 17 August 2022

Abstract

The current research work proposed a novel optimization-based 2D-SIMM (Two-Dimensional Sine Iterative chaotic map with infinite collapse Modulation Map) model for image encryption. The proposed 2D-SIMM model is derived out of sine map and Iterative Chaotic Map with Infinite Collapse (ICMIC). In this technique, scrambling effect is achieved with the help of Chaotic Shift Transform (CST). Chaotic Shift Transform is used to change the value of pixels in the input image while the substituted value is cyclically shifted according to the chaotic sequence generated by 2D-SIMM model. These chaotic sequences, generated using 2D-SIMM model, are sensitive to initial conditions. In the proposed algorithm, these initial conditions are optimized using JAYA optimization algorithm. Correlation coefficient and entropy are considered as fitness functions in this study to evaluate the best solution for initial conditions. The simulation results clearly shows that the proposed algorithm achieved a better performance over existing algorithms. In addition, the VLSI implementation of the proposed algorithm was also carried out using Xilinx system generator. With optimization, the correlation coefficient was −0.014096 and without optimization, it was 0.002585.

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Keywords

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