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Detection of steganography inserted by OutGuess and steghide by means of neural networks

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dc.title Detection of steganography inserted by OutGuess and steghide by means of neural networks en
dc.contributor.author Komínková Oplatková, Zuzana
dc.contributor.author Hološka, Jiří
dc.contributor.author Zelinka, Ivan
dc.contributor.author Šenkeřík, Roman
dc.relation.ispartof 2009 Third Asia International Conference on Modelling & Simulation, Vols 1 and 2
dc.identifier.isbn 978-1-4244-4154-9
dc.date.issued 2009
dc.citation.spage 7
dc.citation.epage 12
dc.event.title 3rd Asia International Conference on Modelling and Simulation
dc.event.location Bundang
utb.event.state-en Indonesia
utb.event.state-cs Indonésie
dc.event.sdate 2009-05-25
dc.event.edate 2009-05-29
dc.type conferenceObject
dc.language.iso en
dc.publisher The Institute of Electrical and Electronics Engineers (IEEE) en
dc.identifier.doi 10.1109/AMS.2009.28
dc.relation.uri http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5071949
dc.description.abstract The paper deals with defection 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 it? 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. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1001849
utb.identifier.rivid RIV/70883521:28140/09:63507970!RIV10-MSM-28140___
utb.identifier.obdid 43861044
utb.identifier.scopus 2-s2.0-70349746792
utb.identifier.wok 000271349800001
utb.source d-wok
dc.date.accessioned 2011-08-09T07:34:05Z
dc.date.available 2011-08-09T07:34:05Z
utb.contributor.internalauthor Komínková Oplatková, Zuzana
utb.contributor.internalauthor Hološka, Jiří
utb.contributor.internalauthor Zelinka, Ivan
utb.contributor.internalauthor Šenkeřík, Roman
utb.fulltext.affiliation Zuzana Oplatková, Jiri Holoska, Ivan Zelinka, Roman Senkerik Faculty of Applied Informatics Tomas Bata University in Zlin Nad Stranemi 4511, 762 72 Zlin Czech Republic {Oplatkova, Holoska, Zelinka, Senkerik}@fai.utb.cz
utb.fulltext.dates -
utb.fulltext.references [1] Radcliff D.: Steganography: Hidden Data, June 10, 2002, http://www.computerworld.com/securitytopics/security/story/0,10801,71726,00.html [2] Bailey K., Curran K.: Steganography, BookSurge Publishing, 2005, ISBN: 159457667X [3] Steganography, cited 2008-03-20, http://en.wikipedia.org/wiki/Steganography [4] Wayner P.: Disappearing Cryptography, Morgan Kaufmann, 2002, ISBN: 1558607692 [5] Software OutGuess, www.outguess.org [6] Defending Against Statistical Steganalysis Niels Provos, 10th USENIX Security Symposium. Washington, DC, August 2001 [7] Hetzl S.: Steghide (1) - Linux man page, cited 2008-05-21, http://steghide.sourceforge.net/documentation/manpage.php [8] Benes M.: Komprese: Huffmanovo kódování, cited 2008-02-15, http://www.cs.vsb.cz/benes/vyuka/pte/texty/komprese/ch02s02.html [9] Neural Network Theory: Feedforward neural networks. Mathematica: Neural nets toolbox: Help [10] Oplatkova Z., Holoska J., Zelinka I., Senkerik R.: Steganography Detection by means of Neural Networks, workshop ETID 2008, In.: DEXA2008, 1-5 September 2008, Turin, Italy, IEEE Computer Society 2008, ISBN 978-0-7695-3299-8 [11] Holoska J., Odhalování steganografie pomocí neuronových sítí, diploma thesis in Czech edition, UTB Zlín, 2008 [12] Oplatkova Z., Holoska J., Zelinka I., Senkerik R.: Detection of Steganography Content Inserted by Steghide by means of Neural Networks, Mendel 2008, ISBN: 978-80-214-3675-6
utb.fulltext.sponsorship This work was supported by the grant NO. MSM 7088352101 of the Ministry of Education of the Czech Republic and by grants of Grant Agency of Czech Republic GACR 102/09/1680.
utb.fulltext.projects MSM 7088352101
utb.fulltext.projects GACR 102/09/1680
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