Evidence map›Paper›PMID 36192488›Full record

ArticleScientific reports2022

High-quality restoration image encryption using DCT frequency-domain compression coding and chaos.

Heping Wen, Linchao Ma, Linhao Liu, Yiming Huang, Zefeng Chen, Rui Li, Zhen Liu, Wenxing Lin, Jiahao Wu, Yunqi Li and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2022. 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

11 authors.

Heping WenZhongshan Institute, School of electronic information, University of Electronic Science and Technology of China, Zhongshan, 528402, China. wenheping@uestc.edu.cn.ORCID http://orcid.org/0000-0002-1178-4598
Linchao MaZhongshan Institute, School of electronic information, University of Electronic Science and Technology of China, Zhongshan, 528402, China.
Linhao LiuZhongshan Institute, School of electronic information, University of Electronic Science and Technology of China, Zhongshan, 528402, China.
Yiming HuangZhongshan Institute, School of electronic information, University of Electronic Science and Technology of China, Zhongshan, 528402, China.
Zefeng ChenZhongshan Institute, School of electronic information, University of Electronic Science and Technology of China, Zhongshan, 528402, China.
Rui LiZhongshan Institute, School of electronic information, University of Electronic Science and Technology of China, Zhongshan, 528402, China.
Zhen LiuZhongshan Institute, School of electronic information, University of Electronic Science and Technology of China, Zhongshan, 528402, China.
Wenxing LinZhongshan Institute, School of electronic information, University of Electronic Science and Technology of China, Zhongshan, 528402, China.
Jiahao WuZhongshan Institute, School of electronic information, University of Electronic Science and Technology of China, Zhongshan, 528402, China.
Yunqi LiZhongshan Institute, School of electronic information, University of Electronic Science and Technology of China, Zhongshan, 528402, China.
Chongfu ZhangSchool of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China. cfzhang@uestc.edu.cn.

Funding

National Science Foundation of China 61571092National Science Foundation of China 62071088Opening Project Guangdong Province Key Laboratory of Information Security Technology 2020B1212060078Project for Innovation Team of Guangdong University 2018KCXTD033Project for Zhongshan Social Public Welfare Science and Technology 2019B2007Research Project for Talent of UESTC Zhongshan Institute 418YKQN07Science and Technology Projects of Guangdong Province 2021A0101180005
6 · The paper itself

Abstract

With the arrival of the age of big data, the amount and types of data in the process of information transmission have increased significantly, and the full-disk encryption mode used by traditional encryption algorithms has certain limitations of the times. In order to further improve the bandwidth efficiency of digital images in the transmission process and the information effectiveness of digital image transmission, this paper proposes an algorithm of high-quality restoration image encryption using DCT frequency-domain compression coding and chaos. Firstly, the image hash value is used for the generation of an encryption key with plaintext correlation, then lightweight chaos is generated based on the key to obtain a pseudo-random sequence. Secondly, the image is partitioned into subblock, and converted from time domain into frequency domain by employing Discrete Cosine Transform (DCT) on each block, then perform quantization operation based on frequency domain information to obtain DCT coefficient matrix. Thirdly, the direct current (DC) coefficients and alternating current (AC) coefficients are extracted in the DCT coefficient matrix and compressed by different encoding methods to obtain two sets of bitstream containing DC coefficient and AC coefficient information. Fourthly, permute the DC coefficient bit stream by the chaotic sequence, and reconstruct it with the AC coefficient bit stream to obtain the frequency domain ciphertext image. Finally, the chaotic sequence is used to diffuse ciphertext, and the processed hash value is hidden in the ciphertext to obtain the final ciphertext. The theoretical and experimental analysis showed that the key length reaches 341 bits, and the PSNR value of the restored image is close to 60, all of which satisfy the theoretical value. Therefore, the algorithm has the characteristics of high compression rate, high-quality image restoration large key space, strong plaintext sensitivity, strong key sensitivity and so on. Our method proposed in this paper is expected to provide a new idea for confidential and secure communication in the age of big data.

Identifiers

PMID36192488
PMCPMC9530123

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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.