Spiral-Transform-Based Fractal Sorting Matrix for Chaotic Image Encryption

Chaotic image encryption is widely used in the field of information security. This paper proposes a novel chaotic image encryption method with spiral-transform-based fractal sorting matrix (STFSM). First of all, the theory of STFSM with good scrambling effect is introduced, which has good irregulari...

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Bibliographic Details
Published in:IEEE transactions on circuits and systems. I, Regular papers Regular papers, 2022-08, Vol.69 (8), p.3320-3327
Main Authors: Xian, Yongjin, Wang, Xingyuan, Wang, Xiaoyu, Li, Qi, Yan, Xiaopeng
Format: Article
Language:English
Subjects:
Algorithms
Chaos
chaotic image encryption
Correlation analysis
Encryption
fractal
Fractal transforms
Fractals
iteration
Iterative algorithms
Security
Sorting
Spiral-transform-based fractal sorting matrix
Spirals
Technological innovation
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Summary:Chaotic image encryption is widely used in the field of information security. This paper proposes a novel chaotic image encryption method with spiral-transform-based fractal sorting matrix (STFSM). First of all, the theory of STFSM with good scrambling effect is introduced, which has good irregularity and iterative. Then, the iterative algorithm and calculation example of STFSM are introduced. STFSM can be used as the map of spatial location transformations to implement the design of image encryption. Based on the complete STFSM theory and iterative algorithm, a chaotic image cryptosystem based on STFSM is proposed to achieve a good image encryption process. To test the security of the proposed algorithm, security tests and analyses such as entropy analysis, correlation analysis, resistance to differential attacks analysis, and robustness analysis are used for the proposed algorithm. The experimental analysis illustrates that the algorithm has a better encryption effect, whether using conventional tests or the attacks simulations described in this paper and can also effectively resist the attacks.
ISSN:1549-8328
1558-0806
DOI:10.1109/TCSI.2022.3172116