Comparison between Neural Network Steganalysis and Linear Classification Method Stegdetect

Steganography is an additional method leading to better securing messages up which goes hand by hand with the cryptography. This is the reason why revealing of such a message is difficult because a final steganogram uses multimedia or other transportation media along with genuine functionality. This paper deals with a blind steganalysis based on a universal neural network classification and compares it to Stegdetect - a linear classification tool. The results show that neural networks were better than the linear classification tool. The worst result was 1% in the case of neural network compared to Stegdetect where 4% was normal and 7.5% was the worst one on the same samples.