An anti-forensic scheme on computer graphic images and natural images using generative adversarial networks.

Computer graphic images (CGI) can be manufactured very similar to natural images (NI) by state-of-the-art algorithms in computer graphic filed. Thus, there are various identification algorithms proposed to detect CGI. However, the manipulation is complicated and difficult for an ultimate CGI against the forensic algorithms.

Information hiding based on Augmented Reality.

Information hiding aims to achieve secret communication via certain carrier. However, these carrier-based methods often have different kinds of deficiencies. In order to solve the problems addressed by the traditional information hiding methods such as the difficult balance between secret embedding rate and detection rate, this paper proposes a novel approach which utilizes Augmented Reality (AR) to achieve secret communication.

A high-capacity coverless image steganography method based on double-level index and block matching.

Recently, a new information hiding technology called coverless information steganography (CIS) is proposed, which uses the original natural image as stego image for the transmission of secret information which can resist the detection of image steganalysis algorithm, so it received extensive attention and support. However, it is still a low hidden capacity of the CIS methods up to now. This paper proposes a high-capacity coverless information steganography technology.