Steganography content detection by means of feedforward neural network

Authors:
Zuzana Komínková Oplatková;Jiří Hološka;Roman Šenkeřík
Affiliations:
Faculty of Applied Informatics, Tomas Bata University, Nam. T.G. Masaryka 5555, 760 01, Zlín, Czech Republic;Faculty of Applied Informatics, Tomas Bata University, Nam. T.G. Masaryka 5555, 760 01, Zlín, Czech Republic;Faculty of Applied Informatics, Tomas Bata University, Nam. T.G. Masaryka 5555, 760 01, Zlín, Czech Republic
Venue:
International Journal of Innovative Computing and Applications
Year:
2013

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Abstract

This paper describes the technique for revealing of steganography content in images by means of feedforward neural network. The work is connected with cryptography for information encoding and additional method for information hiding, which is called steganography. The substance of the paper explains the principle of hidden information detection in images like JPEG format by means of feedforward neural network. The results show successful detection of four stego techniques by means of artificial neural network with one hidden layer.