Back to Search
Start Over
Color Image Cryptosystem Based on Sine Chaotic Map, 4D Chen Hyperchaotic Map of Fractional-Order and Hybrid DNA Coding
- Source :
- IEEE Access, Vol 11, Pp 54928-54956 (2023)
- Publication Year :
- 2023
- Publisher :
- IEEE, 2023.
-
Abstract
- With advancements in computer and communication technologies, the production, utilization and applications of digital images is at an unprecedented rate. Recent applications include military communications, remote sensing, novel engineering designs storage and communications, as well as medical imaging. In most cases, such images convey highly sensitive or confidential information, which creates a strong need for the design of secure and robust color image cryptosystems. Recent literature has shown that fractional-order functions exhibit improved performance over their corresponding integer-order versions. This is especially true in their use in image processing applications. In this research work, we make use of a four-dimensional (4D) hyperchaotic Chen map of fractional-order, in conjunction with a sine chaotic map and a novel hybrid DNA coding algorithm. A thorough numerical analysis is presented, showcasing the security performance and efficiency of the proposed color image cryptosystem. Performance is gauged in terms of resilience against visual, histogram, statistical, entropy, differential, as well as brute-force attacks. Mean values of the metrics computed are as follows. MSE of 9396, PSNR of 8.27 dB, information entropy of 7.997, adjacent pixel correlation coefficient of 0, NPCR of 99.62%, UACI of 33, MAE of 80.57, and a very large key space of 2744. The proposed image cryptosystem exhibits low computational complexity, as it encrypts images at a rate of 4.369 Mbps. Furthermore, it passes the NIST SP 800 suite of tests successfully. Comparison of the computed metrics of the proposed image cryptosystem against those reported in the state-of-the-art by counterpart algorithms show that the proposed cryptosystem exhibits comparable or superior values.
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 11
- Database :
- Directory of Open Access Journals
- Journal :
- IEEE Access
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.98a715c03b34407d835fac5b24b95fc3
- Document Type :
- article
- Full Text :
- https://doi.org/10.1109/ACCESS.2023.3282160