Image steganography without embedding by carrier secret information for secure communication in networks.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2024
Historique:
received: 22 04 2024
accepted: 15 07 2024
medline: 6 9 2024
pubmed: 6 9 2024
entrez: 6 9 2024
Statut: epublish

Résumé

Steganography, the use of algorithms to embed secret information in a carrier image, is widely used in the field of information transmission, but steganalysis tools built using traditional steganographic algorithms can easily identify them. Steganography without embedding (SWE) can effectively resist detection by steganography analysis tools by mapping noise onto secret information and generating secret images from secret noise. However, most SWE still have problems with the small capacity of steganographic data and the difficulty of extracting the data. Based on the above problems, this paper proposes image steganography without embedding carrier secret information. The objective of this approach is to enhance the capacity of secret information and the accuracy of secret information extraction for the purpose of improving the performance of security network communication. The proposed technique exploits the carrier characteristics to generate the carrier secret tensor, which improves the accuracy of information extraction while ensuring the accuracy of secret information extraction. Furthermore, the Wasserstein distance is employed as a constraint for the discriminator, and weight clipping is introduced to enhance the secret information capacity and extraction accuracy. Experimental results show that the proposed method can improve the data extraction accuracy by 10.03% at the capacity of 2304 bits, which verifies the effectiveness and universality of the method. The research presented here introduces a new intelligent information steganography secure communication model for secure communication in networks, which can improve the information capacity and extraction accuracy of image steganography without embedding.

Identifiants

pubmed: 39240910
doi: 10.1371/journal.pone.0308265
pii: PONE-D-24-16179
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0308265

Informations de copyright

Copyright: © 2024 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Auteurs

Yangwen Zhang (Y)

State Key Laboratory of Public Big Data, Guizhou University, Guiyang, China.
College of Computer Science and Technology, Guizhou University, Guiyang, China.

Yuling Chen (Y)

State Key Laboratory of Public Big Data, Guizhou University, Guiyang, China.
College of Computer Science and Technology, Guizhou University, Guiyang, China.

Hui Dou (H)

State Key Laboratory of Public Big Data, Guizhou University, Guiyang, China.
College of Computer Science and Technology, Guizhou University, Guiyang, China.

Chaoyue Tan (C)

State Key Laboratory of Public Big Data, Guizhou University, Guiyang, China.

Yun Luo (Y)

State Key Laboratory of Public Big Data, Guizhou University, Guiyang, China.

Haiwei Sang (H)

Guizhou Education University, Guiyang, China.

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Classifications MeSH