Evidence map›Paper›PMID 37372242›Full record

ArticleEntropy (Basel, Switzerland)2023

A Multiple-Medical-Image Encryption Method Based on SHA-256 and DNA Encoding.

Junfeng Wu, Jialu Zhang, Dong Liu, Xiaofeng Wang

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

4 authors.

Junfeng WuDepartment of Applied Mathematics, Xi'an University of Technology, Xi'an 710049, China.ORCID 0000-0003-4097-6799
Jialu ZhangDepartment of Applied Mathematics, Xi'an University of Technology, Xi'an 710049, China.
Dong LiuDepartment of Applied Mathematics, Xi'an University of Technology, Xi'an 710049, China.
Xiaofeng WangDepartment of Applied Mathematics, Xi'an University of Technology, Xi'an 710049, China.

Funding

National Natural Science Foundation of China 61976176Natural Science Basic Research Program of Shaanxi Province 2022JM-017
6 · The paper itself

Abstract

Ensuring the privacy and secrecy of digital medical images has become a pressing issue as a result of the quick development of smart medical technology and the exponential growth in the quantity of medical images transmitted and stored in networks. The lightweight multiple-image encryption approach for medical images that is suggested in this research can encrypt/decrypt any number of medical photos of varied sizes with just one encryption operation and has a computational cost that is similar to encrypting a single image. The plaintext images with different sizes are filled at the right and bottom of the image to ensure that the size of all plaintext images is uniform; then, all the filled images are stacked to obtain a superimposed image. The initial key, which is generated using the SHA-256 technique, is then used as the starting value of the linear congruence algorithm to create the encryption key sequence. The cipher picture is then created by encrypting the superimposed image with the encryption key and DNA encoding. The algorithm can be made even more secure by implementing a decryption mechanism that decrypts the image independently in order to reduce the possibility of information leaking during the decryption process. The outcomes of the simulation experiment demonstrate the algorithm's strong security and resistance to interference such as noise pollution and lost image content.

Indexed as

DNA encodinghash functionlinear congruencemedical image encryptionmultiple-image encryption

Identifiers

PMID37372242
PMCPMC10296823

What OpenQuestion holds

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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.