JPEG steganalysis using HBCL statistics and FR index
PAISI'10 Proceedings of the 2010 Pacific Asia conference on Intelligence and Security Informatics
Steganography content detection by means of feedforward neural network
International Journal of Innovative Computing and Applications
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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 up. Cryptography, on the other hand, can be and is very often used by jailbirds, so cryptanalysts have also very important job to detect and reveal and then decode the coded messages. Steganography is additional method leading to better secure up messages which goes hand by hand with cryptography, that why reveal of such a message is not easy. This paper deals with neural network models that are able to detect steganography content coded by a program OutGuess. Neural networks are methods which are very flexible in learning to different and difficult problems. Results in this article show that used model had almost 100 % success in revealing steganography by means of OutGuess.