Steganography Based Approach to Image Authentication

The paper is focused on the proposed model of image authentication. The model is based on the steganography principle using a neural network, symmetric encryption and cryptographic hash functions. A key element of the software module is the Optimized Pulse-Coupled Neural Network Model (OM-PCNN). The neural network generates position matrices for embedding authentication data into the cover images with an emphasis on image entropy. In order to increase the security of the proposed solution, the neural network weights are initialized using a steganographic key and, in addition, the authentication data is encrypted by the AES-256 algorithm. Image integrity is tested using SHA-2 hash function with 512-bit hash.