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

  • Xiaojun Tong
  • , Xilin Liu*
  • , Miao Zhang
  • , Zhu Wang
  • *Corresponding author for this work
  • School of Computer Science and Technology, Harbin Institute of Technology
  • School of Information Science and Engineering, Harbin Institute of Technology Weihai

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number115581
JournalChaos, Solitons and Fractals
Volume188
DOIs
StatePublished - Nov 2024
Externally publishedYes

Keywords

  • Adaptive embedding
  • Conservative chaotic system
  • Optimization local binary pattern
  • Two-dimensional compressive sensing

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