Detection of steganography content inserted by Steghide by means of neural networks

Abstract

Cryptography is one of very much spoken word nowadays. Security of messages transfer is very important and specialists have a work to think a new cryptography tip. Cryptography, on the other hand, is used by jailbirds, so cryptanalysts have also very important job to detect and reveal and then decode the coded messages. Steganography is an additional method leading to better secure up messages which goes hand by hand with cryptography, therefore reveal of such a message is not easy. This paper deals with neural network models which are able to detect steganography content coded by a program Steghide using neural networks like taxonomist. Neural networks are methods which are very flexible in learning to different and difficult problems. Results in this paper show that used model had almost 100 % success in revealing steganography by means of Steghide.