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A novel chaotic-based image encryption scheme using multi-layer confusion and conditional diffusion

delete2025-05-01
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PRE
AI
W
Wajid Ali
Z
Zuping Zhang *
M
Muhammad Hussain
DOI:10.1016/j.compeleceng.2025.110402delete
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Abstract

Abstract

En 中文
In the era of digital communication, ensuring the security and efficiency of digital images has become a critical concern. This article proposes a novel three-stage scheme for encrypting images to address high-complexity and low-efficiency issues. First, the Secure Hash Algorithm-256 (SHA-256) is used to initialize an Intertwining Logistic Map (ILM), ensuring plaintext sensitivity and resistance to known chosen-text attacks. In the next confusion phase, a concentric-layer pixel-shuffling pattern is introduced to enhance the randomness of the image data. This pattern divides image pixels into different circular layers, with the number of layers determined by half of the square image's size. To achieve complete randomness, zigzag shuffling is then applied. Finally, a condition-based diffusion approach integrates chaotic sequences with the confused image. If the selected chaotic sequence value is odd, DNA-based diffusion is performed between the confused image and the DNA-encoded masked image generated by the chaotic sequence of ILM; otherwise, an exclusive OR (XOR) operation is applied between the confused image and a chaotic sequence of ILM. The results of the XOR and DNA operations are then combined to generate the cipher image. The average entropy is 7.9973, NPCR is 99.62%, UACI is 33.46%, and the correlation is close to 0. The key space exceeds 10105, suggesting strong security. The proposed scheme improves efficiency, strengthens encryption against cryptanalytic attacks, and improves the practical applicability of the proposed image cipher.
Keywords:
Layers
Bidirectional shuffling
Chaotic map
DNA encoding
SHA-256
Conditional diffusion

Journal

C
Computers and Electrical Engineering
IF:
4.9
Papers:
6.7K
Citations:
1.3W

Organization

Q
Quaid I Azam University
Scholars:
8.5K
Papers: 7.1K
Citations: 55