A Plain-Image-Related Chaotic Image Encryption Algorithm Based on DNA Sequence Operation and Discrete Logarithm
Open accessAbstract
According to the research works of the literatures on chaotic cryptanalysis, many recent chaotic image encryption algorithms cannot resist chosen-plaintext attack. Although some chaotic image encryption algorithms introduce plain-image information, they still violate some design requirements of modern cryptosystems. Therefore, after analyzing many literatures related to chaotic image encryption, we propose a plain-image-related chaotic image encryption algorithm based on the deoxyribonucleic acid (DNA) sequence operation and discrete logarithm. As we know, the discrete logarithm calculation is a complex non-linear calculation, introducing it can increase the complexity of the encryption process. More importantly, discrete logarithm values are significantly different under different generators, and the multiplicative group adopted in the proposed algorithm has as many as 128 generators. Therefore, by using two generators determined by the secret key and the hash value of the plain-image respectively, we not only expand the key space, but also greatly improve the plain-image sensitivity and plain-image relevancy of the encryption process. In addition, the proposed algorithm improves the way of using the hash value of the plain-image. In this way, once the secret key is selected, chaotic sequences can be generated in advance and reused to improve the encryption efficiency. Similarly, the proposed algorithm also introduces the DNA sequence operation with high parallelism to further improves the encryption efficiency. Simulation tests and comparative analyses show that the proposed algorithm can not only resist common attacks, but also outperform some recent chaotic image encryption algorithms in many aspects.
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Chaotic systems are highly suitable for cryptographic applications because of their extreme sensitivity to initial conditions, long-term unpredictability, and strong pseudorandomness.
“Chaotic systems are characterised by their extreme sensitivity to initial conditions and system parameters, resulting in extreme complexity, deterministic and nonlinear characteristics. These properties render chaotic systems highly suitable for cryptographic applications”
From A novel memristor-based hyperchaotic hybrid encryption system with DNA for image encryption on the Jetson TX2 (2025) · cites this paper as [7]
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- YIGANG HE received the M.Sc. degree in electri- cal engineering from Hunan University, Changsha, China, in 1992, and the Ph.D. degree in electri- cal engineering from Xi'an Jiaotong University, Xi'an, China, in 1996. From 2011 to 2017, he was the Head of the School of Electrical Engineering and Automa- tion, Hefei University of Technology. In Decem- ber 2017, he joined Wuhan University, China, where he is currently the Vice-Head of the School of Electrical Engineering and Automation. Meanwhile, he was the Vice President of the China's Energy Institute of Science and Technology and the Anhui Scientists Entrepreneurs Association, and the Director of the State Local Joint Engineering Laboratory for Renewable Energy Grid Technology. In his research areas, he has presided over a number of state-level research projects of the National Natural Science Foundation of China, the State Key Program of National Natural Science Foundation of China, the National Key Research and Development Plan (important scientific instruments and equipment development), the National High Technology Research and Development Program of China, and the Major State Basic Research Devel- opment Program of China. He has published some 300 journal articles and conference papers that include more than 1000 times in Science Citation Index of the American Institute for Scientific Information in the his research areas and several chapters in edited books. His teaching and research interests include power electronic circuit theory and its applications, testing and fault diagnosis of analog and mixed-signal circuits, electrical signal detection, smart grids, satellite communication monitoring, and intelligent signal pro- cessing.
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- Authors
- Feng, W., He, Y., Li, H., & Li, C.
- Affiliations
- Wuhan University (CN)
- Hunan Institute of Science and Technology (CN)
- Venue
- IEEE Access
- Published
- 2019
- Volume
- 7
- Pages
- 181589-181609
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2997684262
- Cited by
- 33
- References
- 66
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 2 · 2023: 9 · 2022: 9 · 2021: 6 · 2020: 3
- FWCI
- 2.01
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Access (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Natural Science Foundation of China (51977153, 51577046)
- State Key Program of National Natural Science Foundation of China (51637004)
- National Key Research and Development Plan (2016YFF0102200)
- Equipment Research Project in Advance (41402040301)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Chaos-based Image/Signal Encryption
- Physical Sciences › Computer Science › Artificial Intelligence › Computer Science and Engineering
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Steganography and Watermarking Techniques
- Keywords
- chaotic image encryption, discrete logarithm problem, chosen-plaintext attack resistance, key space expansion, parallel encryption, encryption efficiency
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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