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Cited by 79Chaos-based Image/Signal EncryptionComputer Science and EngineeringAdvanced Steganography and Watermarking Techniques

R 3—Rescale, Rotate, and Randomize: A Novel Image Cryptosystem Utilizing Chaotic and Hyper-Chaotic Systems

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Gabr, Mohamed, Korayem, Yousef, Chen, Yen-Lin, Yee, Por Lip, Ku, Chin Soon, Alexan, Wassim·2023·IEEE Access
DOI 10.1109/access.2023.3326848
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Abstract

This work proposes a novel image encryption algorithm that integrates unique image transformation techniques with the principles of chaotic and hyper-chaotic systems. By harnessing the unpredictable behavior of the Chua system and the hyper-chaotic nature of the Chen system, the algorithm carries out rescaling, rotation, and randomization on the target image. The intrinsic unpredictability and sensitivity to initial conditions of these chaotic systems endow the encryption algorithm with an expansive key space of 25208. This feature not only bolsters its resilience against brute-force attacks but also magnifies its overall security profile. The algorithm’s efficiency is evident in its rapid computational speed and lean resource consumption, making it suitable for real-time applications. To gauge its robustness, a battery of rigorous tests and analyses, spanning differential attacks, statistical attacks, and brute-force assaults, were employed. The results validate its ability to resist a diverse spectrum of threats. With its expansive key space, exceptional efficiency, and sturdy defenses, the proposed algorithm emerges as a potential cornerstone for safeguarding digital images in arenas like secure communication, data storage, and multimedia transmission. In sum, this research pushes the boundaries of high-security image encryption methodologies, catering to the burgeoning demands of the digital age.

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  • The proposed scheme has an encryption time of 0.2817s, significantly faster than 0.7528s in reference 20 and 3.0019s in reference 30.

    “The results in Table 16 highlight the superior computational efficiency of the proposed scheme, with an encryption time of 0.2817s, significantly faster than 0.7528s in20 and 3.0019s in30.”

    From A chaos-based augmented image encryption scheme for satellite images using Fredkin logic (2025) · cites this paper as [20]

    The paper’s Encryption Time Analysis (§12; page unavailable) reports a sub-one-second encryption time for its R³ scheme on a 256×256 image and says it outperformed all but one compared algorithm. Our copy does not give the claimed times of 0.2817 s, 0.7528 s, or 3.0019 s, or establish the stated comparison; its Table 16 concerns NIST randomness tests, not encryption time. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 50

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  47. Mohamed received his BSc, MSc, and PhD in Computer Science and Engineering from the German University in Cairo (GUC), Egypt, respectively in 2011, 2013, and 2023. He was with the Computer Science and Engi- neering department from 2011 until now. He is teaching various courses in relation to computer vision, artificial intelligence, compilers, theory of computation, and computer graphics. He is the author or co-author of various journal articles and conference papers. His research interests lie in the fields of computer vision and information security.
  48. Dr. Gabr has been granted a Best Paper Award at the 26th IEEE Con- ference on Signal Processing Algorithms, Architectures, Arrangements and Applications, SPA'2023 in Poznan, Poland YOUSEF KORAYEM (SM'23) was born in Cairo, Egypt, in 2001. Yousef defended his BSc thesis in 2023 in Computer Science and Engineer- ing from the German University in Cairo (GUC), Egypt.His research interests lie in the fields of in- formation security and image processing. He has, as of yet, published a number of IEEE conference papers.
  49. YEN-LIN CHEN (SENIOR MEMBER, IEEE) received the B.S. and Ph.D. degrees in electrical and control engineering from the National Chiao Tung University, Hsinchu, Taiwan, in 2000 and 2006, respectively. From February 2007 to July 2009, he was an Assistant Professor at the Depart- ment of Computer Science and Information Engi- neering, Asia University, Taichung, Taiwan. From August 2009 to January 2012, he was an Assistant Professor at the Department of Computer Science and Information Engineering, National Taipei University of Technology, Taipei, Taiwan, where he was an Associate Professor from February 2012 to July 2015, and since August 2015, he has been a Full Professor with the National Taipei University of Technology. His research interests include artificial intelligence, intelligent image analytics, embedded systems, pattern recognition, intelligent vehicles, and intelligent transportation systems. His research results have been published in over 100 journals and conference papers. He is a fellow of the IET and a member of ACM, IAPR, and IEICE.
  50. POR LIP YEE (SENIOR MEMBER, IEEE) received the B.Sc., M.Sc., and Ph.D. degrees from Universiti Malaya, Malaysia. He is currently an Associate Professor at the Faculty of Computer Science and Information Technology, Universiti Malaya. His research interests include neural net- works (such as supervised and unsupervised learn- ing methods, such as support vector machine and extreme learning machine), bioinformatics (such as biosensors and pain research), computer secu- rity [such as information security, steganography, and authentication (graph- ical password)], grid computing, and e-learning framework.

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Authors
Gabr, M., Korayem, Y., Chen, Y.-L., Yee, P. L., Ku, C. S., & Alexan, W.
Affiliations
  • German University in Cairo (EG)
  • National Taipei University of Technology (TW)
  • Department of Computer System and Technology, Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur, Malaysia
  • Universiti Tunku Abdul Rahman (MY)
  • German International University (EG)
ORCID
Venue
IEEE Access
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2023
Volume
11
Pages
119284-119312
ISSN
2169-3536 (ISSN-L)
DOI
10.1109/access.2023.3326848
OpenAlex
W4387886044
Cited by
79
References
2
Citations by year
2026: 16 · 2025: 36 · 2024: 26 · 2023: 1
FWCI
7.18
Type
journal article
Language
en
Open access
Licence
Locations
  • IEEE Access (publishedVersion, cc-by-nc-nd)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Science and Technology Council in Taiwan (NSTC-111-2622-8-027-009, NSTC-112-2221-E-027-088-MY2)
  • Ministry of Education of Taiwan (1112303249)
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
image encryption, chaotic systems, hyperchaotic systems, Chua system, Chen system, image scaling, image rotation, key space, brute-force attack resistance, differential attack resistance, statistical attack resistance, real-time encryption

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