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  • In the view of global data growth in all industry fields, emphasis should be put on the quality and the information content as well as on the data optimization of processes which work with this data. This paper deals with a possibility to optimize by means of data mining a process of steganalysis solved by neural networks. One of the basic methods of data mining classification can reduce a dimension of data which is performed by NN later. To obtain a datamining model algorithm J48 was used and also several testing methods which classify instances with 64 attributes into two classes. For comparison with the originally published neural networks model, neural networks were used again to verify the data mining model. Conclusion is focused on holding an accuracy of classification and prediction of the model with additional refers to time savings caused by reduction of used data.
  • In the view of global data growth in all industry fields, emphasis should be put on the quality and the information content as well as on the data optimization of processes which work with this data. This paper deals with a possibility to optimize by means of data mining a process of steganalysis solved by neural networks. One of the basic methods of data mining classification can reduce a dimension of data which is performed by NN later. To obtain a datamining model algorithm J48 was used and also several testing methods which classify instances with 64 attributes into two classes. For comparison with the originally published neural networks model, neural networks were used again to verify the data mining model. Conclusion is focused on holding an accuracy of classification and prediction of the model with additional refers to time savings caused by reduction of used data. (en)
Title
  • Datamining Optimization of Steganalysis by means of Neural Network
  • Datamining Optimization of Steganalysis by means of Neural Network (en)
skos:prefLabel
  • Datamining Optimization of Steganalysis by means of Neural Network
  • Datamining Optimization of Steganalysis by means of Neural Network (en)
skos:notation
  • RIV/70883521:28140/10:63508853!RIV11-GA0-28140___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA102/09/1680), S, Z(MSM7088352101)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 252980
http://linked.open...ai/riv/idVysledku
  • RIV/70883521:28140/10:63508853
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Classification; Data mining; Optimization; Steganalysis; Artificial Neural Networks (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [D76310C9D97B]
http://linked.open...v/mistoKonaniAkce
  • Zlín
http://linked.open...i/riv/mistoVydani
  • Zlín
http://linked.open...i/riv/nazevZdroje
  • Internet, bezpečnost a konkurenceschopnost organizací. Řízení procesů a využití moderních teerminálových technologií
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Oplatková, Zuzana
  • Procházka, Michal
  • Hološka, Jiří
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
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  • Univerzita Tomáše Bati ve Zlíně, Fakulta aplikované informatiky
https://schema.org/isbn
  • 978-83-61645-16-0
http://localhost/t...ganizacniJednotka
  • 28140
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