A high-quality visual image encryption algorithm utilizing the conservative chaotic system and adaptive embedding

Xiaojun Tong, Xilin Liu, Miao Zhang and Zhu Wang

Chaos, Solitons & Fractals, 2024, vol. 188, issue C

Abstract: Regarding the issue of encrypted images in the channel attracting the attention of attackers and making them vulnerable to attacks. This paper proposes a high-quality visual image encryption algorithm utilizing the conservative chaotic system, two-dimensional compressive sensing, optimization local of binary patterns, and adaptive embedding method. Firstly, a conservative chaotic system with excellent performance and resistance to reconstruction attacks is proposed. Secondly, the pseudo-random sequences generated by the chaotic system dynamically generate measurement matrices, which are optimized before compressing the image. Then, during the encryption process, by utilizing the newly proposed composite DNA computing rules, chaotic sequences dynamically encode and compute image information, which enriches the coding criteria and improves the security of encryption algorithms. Finally, in the information embedding stage, the newly proposed OLBP algorithm can identify important textured and non-textured regions of the host image, prioritize embedding non-textured regions, and then embed textured regions, which can improve the amount of information embedding and reduce damage to the host image. Experimental simulation and analysis exhibit that the encryption algorithm has high security, strong robustness and high efficiency. Meanwhile the imperceptible analysis of the steganographic images is exceed 52 dB, so the algorithm presents a high-quality visual effect of imperceptibility.

Keywords: Conservative chaotic system; Two-dimensional compressive sensing; Optimization local binary pattern; Adaptive embedding (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:188:y:2024:i:c:s0960077924011330

DOI: 10.1016/j.chaos.2024.115581

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