A Software Model of Masking Hidden Message in Steganography Tasks

The authors deal with the issue of developing a software model for disguising a concealed message in HUGO systems in conditions of affected noise in the connection channel using a discrete random Arnold cat map and a Baker map that are repetitive reverse discrete chaotic transforms. All stages of software model development are considered in detail, such as the choice of the development environment, the composition of software modules and their purpose, screenshots of graphical interfaces for various modes of operation of the model. In a software model to assess the random state of a secret message presented by a digital static picture, the authors enter a chaotic coefficient, a quantitative measure of the entropy of the probabilities of unordered pixels. In the designed software model, the authors suggest a procedure for defining the limit value of the chaotic coefficient corresponding to the limit of the random state of the hidden message. Testing of the software model shows the practical indistinguishability of the transformed hide message from the native noise in the connection channel and greatly improves the security of HUGO stegosystems.