Technology of Information Security
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 1
266-271

Lightweight image steganography scheme based on invertible neural network

Sun Wenquan
Liu Jia
Niu Ke
Dong Weina
Chen Lifeng
Key Laboratory of Network & Information Security under Chinese People Armed Police Force, Engineering University of PAP, Xi'an 710086, China
DOI: 10.19734/j.issn.1001-3695.2023.05.0215

Abstract

At present, the steganographic capacity of deep learning-based steganographic models has been improved, but due to the complexity of the network structure, it requires a lot of time to train. Aiming at this problem, this paper proposed a lightweight invertible neural network structure and used to design an efficient image steganography scheme, which adopted a dense connection-based invertible neural network to achieve image hiding and recovery, and increased the number of convolutional blocks of invertible functions f(·)、r(·) and y(·) in each invertible block to ensure the quality of the image while reducing the number of invertible blocks. It could significantly reduce the computational and storage overheads, making the model run more efficiently on devices with limited computational resources, making the process of model development and iteration more efficient, and effectively saving valuable computational resources. It transformed the cover and the secret image by forward hidden invertible transform to generate the stego image, and transformed the stego image and the random variable by reversing recovery invertible transform to get the recovered image. The experimental results show that compared with HiNet algorithm, the proposed lightweight network structure can achieve good image quality and security, while reducing the training time by 46% and the steganography time by 28%.

Foundation Support

国家自然科学基金面上项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.05.0215
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 1
Section: Technology of Information Security
Pages: 266-271
Serial Number: 1001-3695(2024)01-042-0266-06

Publish History

[2023-10-07] Accepted Paper
[2024-01-05] Printed Article

Cite This Article

孙文权, 刘佳, 钮可, 等. 基于可逆网络的轻量化图像隐写方案 [J]. 计算机应用研究, 2024, 41 (1): 266-271. (Sun Wenquan, Liu Jia, Niu Ke, et al. Lightweight image steganography scheme based on invertible neural network [J]. Application Research of Computers, 2024, 41 (1): 266-271. )

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  • Application Research of Computers Monthly Journal
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    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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