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A color image encryption algorithm for expert detection system based on composite chaotic sequences
Z. Li 1

1 School of Forensic Science and Technology, Criminal Investigation Police University of China,
110854, China, Shenyang, Huanggu District, Tawan Street, 83

 PDF, 1962 kB

DOI: 10.18287/2412-6179-CO-1457

Pages: 95-102.

Full text of article: English language.

Abstract:
With the development of the Internet, the amount of information carried in images is gradually increasing, and image encryption algorithms for data transmission have been developed. The conventional composite chaotic sequence encryption algorithm has the problem of too long convergence speed when applied to images, which can lead to the risk of information leakage in the image. To address this issue, this study first applies chaotic attractors to improve composite chaotic sequences and enhance the search domain of their Leia Index. At the same time, the Arnold transform technology is introduced into the expert monitoring system, and the two systems are fused to generate a fusion algorithm for color image encryption. Finally, the study conducts experiments on the Differ dataset to verify the effectiveness and superiority of the fusion algorithm, and compares it with three algorithms such as artificial fish schools. The image encryption times of the four algorithms are 6 s, 16 s, 29 s, and 33 s respectively, indicating that the fusion algorithm has the highest encryption speed. When facing exhaustive attacks, the image information damage degrees of the four algorithms are 0.014, 0.051, 0.172, and 0.184, respectively. The experimental results show that the proposed algorithm can effectively resist differential attacks and exhaustive attacks, and is suitable for encrypting color images.

Keywords:
composite chaotic sequence, expert detection system, color image encryption, chaotic attractor, Leia index, Arnold transformation.

Citation:
Li Z. A color image encryption algorithm for expert detection system based on composite chaotic sequences. Computer Optics 2025; 49 (1): 95-102. DOI: 10.18287/2412-6179-CO-1457.

Acknowledgements:
The research was supported by the Special Project of Basic Work for Strengthening Police with Science and Technology of the Ministry of Public Security, Project number: No. 2020GABJC03; Basic Scientific Research Projects of Education Department in 2023, Project number: No. JYTZD2023146 and Guangdong Provincial Forensic Science of Evidence Materials (Nantian) Engineering Technology Research Center Open Projects Fund, Project number: ETRC202404.

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