Evidence map›Paper›PMID 37420494›Full record

ArticleEntropy (Basel, Switzerland)2022

A Novel Color Image Encryption Scheme Based on Hyperchaos and Hopfield Chaotic Neural Network.

Yanan Wu, Jian Zeng, Wenjie Dong, Xinyu Li, Danyang Qin, Qun Ding

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Yanan WuElectronic Engineering College, Heilongjiang University, Harbin 150080, China.
Jian ZengElectronic Engineering College, Heilongjiang University, Harbin 150080, China.
Wenjie DongBeijing Aerospace Institute of Automatic Control, Beijing 100854, China.
Xinyu LiElectronic Engineering College, Heilongjiang University, Harbin 150080, China.ORCID 0000-0001-6147-0733
Danyang QinElectronic Engineering College, Heilongjiang University, Harbin 150080, China.
Qun DingElectronic Engineering College, Heilongjiang University, Harbin 150080, China.

Funding

National Natural Science Foundation of China YQ2020F012
6 · The paper itself

Abstract

Problems such as insufficient key space, lack of a one-time pad, and a simple encryption structure may emerge in existing encryption schemes. To solve these problems, and keep sensitive information safe, this paper proposes a plaintext-related color image encryption scheme. Firstly, a new five-dimensional hyperchaotic system is constructed in this paper, and its performance is analyzed. Secondly, this paper applies the Hopfield chaotic neural network together with the novel hyperchaotic system to propose a new encryption algorithm. The plaintext-related keys are generated by image chunking. The pseudo-random sequences iterated by the aforementioned systems are used as key streams. Therefore, the proposed pixel-level scrambling can be completed. Then the chaotic sequences are utilized to dynamically select the rules of DNA operations to complete the diffusion encryption. This paper also presents a series of security analyses of the proposed encryption scheme and compares it with other schemes to evaluate its performance. The results show that the key streams generated by the constructed hyperchaotic system and the Hopfield chaotic neural network improve the key space. The proposed encryption scheme provides a satisfying visual hiding result. Furthermore, it is resistant to a series of attacks and the problem of structural degradation caused by the simplicity of the encryption system's structure.

Indexed as

DNA codingHopfield chaotic neural networkhyperchaotic systemimage encryption

Identifiers

PMID37420494
PMCPMC9601655

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.