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A highly secure image encryption algorithm based on conservative hyperchaotic system and dynamic biogenetic gene algorithms

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  • Liu, Xilin
  • Tong, Xiaojun
  • Zhang, Miao
  • Wang, Zhu

Abstract

Aiming at the problem that the current image encryption algorithms generally use dissipative chaos, which leads to the algorithms being vulnerable to reconstruction attack, and the coding rules of image encryption algorithms using biological coding are too simple, this paper proposes an image encryption algorithm based on conservative hyperchaotic and biological gene algorithms. Firstly, a new conservative hyperchaotic system is proposed, which can resist reconstruction attacks, has a larger key space, and can generate pseudorandom sequences with strong randomicity. Secondly, SHA-512 is used to calculate the hash value of plaintext image, and the initial key is generated through the key generation algorithm we devised to improve the sensitivity of the algorithm to the key and plaintext. Finally, new dynamic coding rules are designed to enrich the biological coding rules. In addition, dynamic gene uniform crossover algorithm and dynamic gene mutation algorithm are devised, and pseudorandom sequences dynamically control gene operation, further enriching coding rules and expanding key space, improving the security of the algorithm. According to experimental and analysis results, the image encryption algorithm has high security and efficiency.

Suggested Citation

  • Liu, Xilin & Tong, Xiaojun & Zhang, Miao & Wang, Zhu, 2023. "A highly secure image encryption algorithm based on conservative hyperchaotic system and dynamic biogenetic gene algorithms," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    • Handle: RePEc:eee:chsofr:v:171:y:2023:i:c:s096007792300351x
    DOI: 10.1016/j.chaos.2023.113450
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    References listed on IDEAS

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    1. Liu, Xilin & Tong, Xiaojun & Wang, Zhu & Zhang, Miao, 2022. "A new n-dimensional conservative chaos based on Generalized Hamiltonian System and its’ applications in image encryption," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).
    2. Liu, Hongjun & Kadir, Abdurahman & Xu, Chengbo, 2020. "Cryptanalysis and constructing S-Box based on chaotic map and backtracking," Applied Mathematics and Computation, Elsevier, vol. 376(C).
    3. Folifack Signing, V.R. & Gakam Tegue, G.A. & Kountchou, M. & Njitacke, Z.T. & Tsafack, N. & Nkapkop, J.D.D. & Lessouga Etoundi, C.M. & Kengne, J., 2022. "A cryptosystem based on a chameleon chaotic system and dynamic DNA coding," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    4. Wang, Xingyuan & Du, Xiaohui, 2022. "Pixel-level and bit-level image encryption method based on Logistic-Chebyshev dynamic coupled map lattices," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
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    1. Long, Guoqiang & Chai, Xiuli & Gan, Zhihua & Jiang, Donghua & He, Xin & Sun, Mengge, 2023. "Exploiting one-dimensional exponential Chebyshev chaotic map and matching embedding for visually meaningful image encryption," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    2. Zou, Chengye & Li, Haifeng & Zhang, Xuncai & Liu, Yunong & Shang, Yubao & Zhou, Chuangjun, 2024. "Target localization image encryption of wind turbines based on DNA strand replacement rule," Chaos, Solitons & Fractals, Elsevier, vol. 183(C).
    3. SaberiKamarposhti, Morteza & Ghorbani, Amirabbas & Yadollahi, Mehdi, 2024. "A comprehensive survey on image encryption: Taxonomy, challenges, and future directions," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).

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