Evidence map›Paper›PMID 33265805›Full record

ArticleEntropy (Basel, Switzerland)2018

A New Image Encryption Algorithm Based on Chaos and Secure Hash SHA-256.

Shuqin Zhu, Congxu Zhu, Wenhong Wang

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. A Note on the Reproducibility of Chaos Simulation.Entropy (Basel, Switzerland) · 2020
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Entropy in Image Analysis.Entropy (Basel, Switzerland) · 2019
    Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Shuqin ZhuSchool of Computer and Science, Liaocheng University, Liaocheng 252059, China.
Congxu ZhuSchool of Information Science and Engineering, Central South University, Changsha 410083, China.ORCID 0000-0002-9662-0532
Wenhong WangSchool of Computer and Science, Liaocheng University, Liaocheng 252059, China.

Funding

National Natural Science Foundation of China 61472451Open Project of Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big DataProcessing 2016CSOBDP0103Shan Dong Province Nature Science Foundation ZR2017MEM019The science Research Fund of Liaocheng University 318011606
6 · The paper itself

Abstract

In order to overcome the difficulty of key management in "one time pad" encryption schemes and also resist the attack of chosen plaintext, a new image encryption algorithm based on chaos and SHA-256 is proposed in this paper. The architecture of confusion and diffusion is adopted. Firstly, the surrounding of a plaintext image is surrounded by a sequence generated from the SHA-256 hash value of the plaintext to ensure that each encrypted result is different. Secondly, the image is scrambled according to the random sequence obtained by adding the disturbance term associated with the plaintext to the chaotic sequence. Third, the cyphertext (plaintext) feedback mechanism of the dynamic index in the diffusion stage is adopted, that is, the location index of the cyphertext (plaintext) used for feedback is dynamic. The above measures can ensure that the algorithm can resist chosen plaintext attacks and can overcome the difficulty of key management in "one time pad" encryption scheme. Also, experimental results such as key space analysis, key sensitivity analysis, differential analysis, histograms, information entropy, and correlation coefficients show that the image encryption algorithm is safe and reliable, and has high application potential.

Indexed as

chaotic systemdynamic indeximage encryptionpermutation-diffusionSHA-256 hash value

Identifiers

PMID33265805
PMCPMC7513242

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.