A novel chaotic image cryptosystem based on DNA sequence operations and single neuron model
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The sensitivity mechanisms of PRNS on the plain-image built in [80,119,27,92] can be easily canceled by constructing special plain-images.
“For example, the sensitivity mechanisms of PRNS on the plain-image built in [80,119,27,92] can be easily canceled by constructing some special plain-images, which has been reported in many cryptanalysis papers such as [1,117].”
From When an attacker meets a cipher-image in 2018: A year in review (2019) · cites this paper as [80]
Cites
Communication Theory of Secrecy Systems
Shannon, C. E. (1949) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1949.tb00928.x · Cited by 9,440 · see citing works
Local Shannon entropy measure with statistical tests for image randomness
Wu, Y., Zhou, Y., Saveriades, G., Agaian, S., Noonan, J. P., & Natarajan, P. (2013) · Information Sciences · doi:10.1016/j.ins.2012.07.049 · Cited by 722 · cited 1× · see citing works
“To test the local randomness of the plain image and the encrypted image, Local Shannon entropy [55] is utilized.”
MethodA fast image encryption system based on chaotic maps with finite precision representation
Kwok, H. S., & Tang, W. K. S. (2007) · Chaos, Solitons & Fractals · doi:10.1016/j.chaos.2005.11.090 · Cited by 428 · see citing works
Security analysis of a chaos-based image encryption algorithm
Lian, S., Sun, J., & Wang, Z. (2005) · Physica A: Statistical Mechanics and its Applications · doi:10.1016/j.physa.2005.01.001 · Cited by 193 · see citing works
Pareschi, F., Rovatti, R., & Setti, G. (2012) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2012.2185227 · Cited by 189 · cited 1× · see citing works
“NIST SP 800-22 [47] is used to test the randomness of encrypted image.”
MethodChaotic Image Encryption Design Using Tompkins-Paige Algorithm
Etemadi Borujeni, S., & Eshghi, M. (2009) · Mathematical Problems in Engineering · doi:10.1155/2009/762652 · Cited by 74 · cited 1× · see citing works
“, require reliable, fast, and robust security system to store and transmit digital images [4, 22, 34, 51].”
Background
Flagged first, then by citations
Cited by
Sorted by citations
When an attacker meets a cipher-image in 2018: A year in review
Li, C., Zhang, Y., & Xie, E. Y. (2019) · Journal of Information Security and Applications · doi:10.1016/j.jisa.2019.102361 · Cited by 217 · see citing works
“In [80], a scheme encrypting optical image is designed with the same strategy as that in [77, 79].”
BackgroundMethod
- Authors
- Ben Slimane, N., Aouf, N., Bouallegue, K., & Machhout, M.
- Affiliations
- University of Monastir (TN)
- Corresponding author
- Aouf, Nahed
- Bouallegue, Kais
- Machhout, Mohsen
- Venue
- Multimedia Tools and Applications
- Published
- 2018-06-04
- Volume
- 77
- Issue
- 23
- Pages
- 30993-31019
- ISSN
- 1380-7501 (ISSN-L)
- 1573-7721
- OpenAlex
- W2805129962
- Cited by
- 51
- References
- 6
- Citations by year
- 2025: 6 · 2024: 9 · 2023: 12 · 2022: 10 · 2021: 5 · 2020: 5 · 2019: 4
- FWCI
- 1.75
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Multimedia Tools and Applications (publishedVersion)
- Funders
- This research is supported by ministry of higher education and scientific research of Tunisia
- 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 maps, single neuron model, confusion and diffusion, keystream generation, key space, sensitivity to initial conditions, correlation analysis, color image encryption
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 ›
Are you an author, or do you see a problem with this page? Request a review
