A Robust Text Information Hiding Model Based On Quick Response Code
Jingyu Wang, Zhijie Yao, Xiaojun Jing, Junsheng Mu · 2023
As an important direction in the field of information hiding, steganography is a significant means to realize secret communication. With the development of artificial intelligence, researchers have tried to use Deep Learning (DL) to design automated information hiding schemes, but the existing schemes still have shortcomings in security, hiding capacity, and robustness. To solve this problem, this paper designs a set of safe and robust image information hiding schemes by using a DL network, Quick Response (QR) coding, and introducing a noise layer mechanism. In addition, this scheme makes information hiding technology get rid of the dependence on human operation and prior professional knowledge, breaks the dilemma that information hiding needs to choose the appropriate hidden carrier and modify the carrier to embed information, and also proves that it has great potential in the field of information security.