An image encryption scheme using self-adaptive selective permutation and inter-intra-block feedback diffusion
Integrity signals
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
A large number of image encryption schemes treat the plain-image as ordinary textual data.
“A large number of image encryption schemes just treat plain-image as an ordinary textual data [5].”
From When an attacker meets a cipher-image in 2018: A year in review (2019) · cites this paper as [5]
Cites
Image quality assessment: from error visibility to structural similarity
Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004) · IEEE Transactions on Image Processing · doi:10.1109/tip.2003.819861 · Cited by 57,892 · 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 · see citing works
A chaos-based symmetric image encryption scheme using a bit-level permutation
Zhu, Z.-L., Zhang, W., Wong, K.-W., & Yu, H. (2011) · Information Sciences · doi:10.1016/j.ins.2010.11.009 · Cited by 662 · see citing works
Self-citationA 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
Chen, J., Zhu, Z.-L., Zhang, L.-B., Zhang, Y., & Yang, B.-Q. (2018) · Signal Processing · doi:10.1016/j.sigpro.2017.07.034 · Cited by 320 · see citing works
Self-citationCircular inter–intra pixels bit-level permutation and chaos-based image encryption
Diaconu, A.-V. (2016) · Information Sciences · doi:10.1016/j.ins.2015.10.027 · Cited by 186 · see citing works
Color image encryption based on chaotic systems and elliptic curve ElGamal scheme
Wu, J., Liao, X., & Yang, B. (2017) · Signal Processing · doi:10.1016/j.sigpro.2017.04.006 · Cited by 183 · see citing works
Flagged first, then by citations
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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
An Image Encryption Method Based on Elliptic Curve Elgamal Encryption and Chaotic Systems
Luo, Y., Ouyang, X., Liu, J., & Cao, L. (2019) · IEEE Access · doi:10.1109/access.2019.2906052 · Cited by 172 · see citing works
Secure Image Transmission Using Chaotic-Enhanced Elliptic Curve Cryptography
Abdelfatah, R. I. (2020) · IEEE Access · doi:10.1109/access.2019.2958336 · Cited by 73 · see citing works
A Robust Image Encryption Algorithm Based on a 32-bit Chaotic System
Li, H., Deng, L., & Gu, Z. (2020) · IEEE Access · doi:10.1109/access.2020.2972296 · Cited by 51 · see citing works
“Therefore, compared with 2WH of [49] and 4WH of [54], this algorithm”
Result
- Authors
- Liu, D.-D., Zhang, W., Yu, H., & Zhu, Z.-L.
- Affiliations
- Northeastern University (CN)
- ORCID
- Yu, Hai
- Venue
- Signal Processing
- Publisher
- Elsevier BV
- Published
- 2018-10
- Volume
- 151
- Pages
- 130-143
- ISSN
- 0165-1684 (ISSN-L)
- OpenAlex
- W2799634971
- Cited by
- 63
- References
- 7
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 4 · 2023: 2 · 2022: 7 · 2021: 19 · 2020: 11 · 2019: 15 · 2018: 1
- FWCI
- 5.76
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Signal Processing (publishedVersion)
- Funders
- National Natural Science Foundation of China (61374178, 61402092)
- 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 › Artificial Intelligence › Cryptographic Implementations and Security
- Keywords
- image encryption, confusion, chaotic maps, differential attack resistance, statistical attack resistance
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.
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