Comparison between Neural Network Steganalysis and Linear Classification Method Stegdetect

  • Authors:
  • Jiri Holoska;Zuzana Oplatkova;Ivan Zelinka;Roman Senkerik

  • Affiliations:
  • -;-;-;-

  • Venue:
  • CIMSIM '10 Proceedings of the 2010 Second International Conference on Computational Intelligence, Modelling and Simulation
  • Year:
  • 2010

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Abstract

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.