Hiding Image within Image Based on Deep Learning

• Published in: Journal of physics. Conference series Vol. 2337; no. 1; pp. 12009 - 12015
• Main Authors: Yang, Pan, Zhang, Minqing, Wu, Riming, Su, Yunxuan, Guo, Kaiyang
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.09.2022
• Subjects: Algorithms; Coders; Deep learning; Design modifications; Encoders-Decoders; Generative adversarial networks; Machine learning; Neural networks; Physics; Steganography
• ISSN: 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/2337/1/012009

Abstract Information hiding technology is a technology that transmits secret information through a carrier, and is a research hotspot in the field of information security. The traditional information hiding algorithm relies on the meticulous design of human beings, and obtains the dense image through modification. With the development of deep learning, the integration of information hiding technology and deep learning has resulted in many information hiding technologies based on deep learning. Among them, image hiding has become a research hotspot due to its large steganographic capacity. Therefore, this paper reviews the information hiding technology based on deep learning. According to the difference of hidden models, it is analysed from four aspects: (1) information hiding model based on encoder-decoder; (2) information hiding model based on generative adversarial network; (3) information hiding model based on invertible network; (4) information hiding model based on neural network information hiding models for style transfer. Finally, these models are analysed and compared, and the future development direction is discussed and prospected.