A Steganography Model Data Protection Method Based on Scrambling Encryption

Abstract

At present, the image steganography method based on CNN has achieved good results. The trained model and its parameters are of great value. Once leaked, the secret image will be exposed. To protect the security of steganographic network model parameters in the transmission process, an idea based on network model parameter scrambling is proposed in this paper. Firstly, the sender trains the steganography network and extraction network, encrypts the extraction network parameters with the key shared by the sender and the receiver, then sends the extraction network and parameters to the receiver through the public channel, and the receiver recovers them with the key after receiving, to achieve more secure secret communication. In this way, even if the network parameters are intercepted by a third party in the transmission process, the interceptor cannot extract the real secret information. In this paper, the classical Joseph algorithm is used as the scrambling algorithm to scramble the extracted network model parameters of the StegoPNet steganography network. The experimental results show that when the scrambled parameters are used for secret image extraction, a meaningless image independent of the secret image is extracted, it shows that this method can well protect the security of steganography network model. At the same time, this method also has good scalability, and can use a variety of different scrambling algorithms to scramble the parameters.