Generative Steganography Based on the Construction of Chinese Chess Record

Steganography is a technique for hiding secret information in imperceptible carriers and transmitting it. Unlike traditional embedding-based steganography, generative steganography can generate stego-carriers directly from secret messages, thus avoiding modifications to natural carriers that steganalysis can detect. As a branch of generative steganography, game-behavior-based steganography transmits secret information by encoding game behavior. It can naturally integrate with real interaction scenarios, exhibiting strong concealment and undetectability. To this end, this paper proposes a generative steganography based on Chinese Chess record construction. Firstly, an AlphaZero model was trained to achieve a high level in Chinese Chess, then transmit secret information by encoding chess behavior. Specifically, in each chess step, the model generates all the current feasible moves and encodes the moves that meet the threshold strategy according to probability. Then, the appropriate move will be selected according to the secret information. To ensure the reasonableness of the generated chess records, this paper controlled the game process and designed a database of fixed opening chess records. The proposed method can hide an average of 413 bits of information for each carrier and effectively resist common image attacks. Regarding anti-steganalysis, the proposed method achieved accuracy rates of 0.498 and 0.497 on XuNet and YeNet, respectively, outperforming other behavior-based steganography techniques.