Robust steganographic method based on unconventional approach of neural networks

Abstract

The article deals with the issue of using an apparatus of neural networks in the area of steganography. A new method called STEGONN was proposed. The proposed method is robust enough to an attack and the hidden message hard to be falsified. The core of our work lies in a design and implementation of a method for the use of neural networks as a native coder and decoder of a secret message (digital watermark) with an emphasis on the minimum necessary level of image data modification – covermedium. A covermedium is not perceived as a passive cover of a secret message, but we make active use of cover medium data, primarily its data markers (image markers) to insert a secret message. The advantage over other steganographic methods is the fact that the method implicitly offer the possibility to detect corrupted parts of the stegomedium and inform the user about possible manipulation with the image. The characteristics of the proposed method have been experimentally verified and compared with commercially available steganographic applications.