Open Access

ARTICLE

Sine-Polynomial Chaotic Map (SPCM): A Decent Cryptographic Solution for Image Encryption in Wireless Sensor Networks

David S. Bhatti^1,*, Annas W. Malik², Haeung Choi¹, Ki-Il Kim^3,*

1 School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Gwangju, 61005, Republic of Korea
2 Faculty of Information Technology & Computer Science, University of Central Punjab, Lahore, 54000, Pakistan
3 Department of Computer Science and Engineering, Chungnam National University, Daejeon, 34134, Republic of Korea

* Corresponding Authors: David S. Bhatti. Email: ; Ki-Il Kim. Email:

Computers, Materials & Continua 2025, 85(1), 2157-2177. https://doi.org/10.32604/cmc.2025.068360

Received 27 May 2025; Accepted 25 July 2025; Issue published 29 August 2025

Abstract

Traditional chaotic maps struggle with narrow chaotic ranges and inefficiencies, limiting their use for lightweight, secure image encryption in resource-constrained Wireless Sensor Networks (WSNs). We propose the SPCM, a novel one-dimensional discontinuous chaotic system integrating polynomial and sine functions, leveraging a piecewise function to achieve a broad chaotic range () and a high Lyapunov exponent (5.04). Validated through nine benchmarks, including standard randomness tests, Diehard tests, and Shannon entropy (3.883), SPCM demonstrates superior randomness and high sensitivity to initial conditions. Applied to image encryption, SPCM achieves 0.152582 s (39% faster than some techniques) and 433.42 KB/s throughput (134% higher than some techniques), setting new benchmarks for chaotic map-based methods in WSNs. Chaos-based permutation and exclusive or (XOR) diffusion yield near-zero correlation in encrypted images, ensuring strong resistance to Statistical Attacks (SA) and accurate recovery. SPCM also exhibits a strong avalanche effect ( bit difference), making it an efficient, secure solution for WSNs in domains like healthcare and smart cities.

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Keywords

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