Geodesic
Forming indicators vectors for neural networks training to detect attacks on web applications
Prikladnaya Diskretnaya Matematika. Supplement, no. 7 (2014), pp. 96-99

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An approach for choosing the most suitable indicators to detect various types of attacks on web applications is described. A method for forming vectors of indicators for classes of attacks is proposed. The method reduces the amount of required neural networks and accelerates the process of attack detection.
Keywords: intrusion detection, misuse detection, neural network, vector of indicators, web application.
Mots-clés : intrusion classes 
@article{PDMA_2014_7_a41,
     author = {S. N. Sorokin},
     title = {Forming indicators vectors for neural networks training to detect attacks on web applications},
     journal = {Prikladnaya Diskretnaya Matematika. Supplement},
     pages = {96--99},
     publisher = {mathdoc},
     number = {7},
     year = {2014},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/PDMA_2014_7_a41/}
}
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S. N. Sorokin. Forming indicators vectors for neural networks training to detect attacks on web applications. Prikladnaya Diskretnaya Matematika. Supplement, no. 7 (2014), pp. 96-99. http://geodesic.mathdoc.fr/item/PDMA_2014_7_a41/