Detection of Steganography Inserted by OutGuess and Steghide by Means of Neural Networks

The paper deals with detection of steganography content. Steganography is an additional method in cryptography which helps to hide coded messages inside pictures or videos. To hide a message is very important but also revealing such content is important to avoid of usage by jailbirds. The revealing of steganography is not easy. This paper shows how neural networks are able to detect steganography content coded by a program OutGuess and Steghide using neural networks like taxonomist. Training sets were created from clear and coded pictures with different length of inserted message. Neural networks are methods which are very flexible in learning to different and difficult problems. Results in this paper show that used models had almost 100 % success in steganography detection of messages inserted by OutGuess and Steghide.