Using SVM and clustering algorithms in IDS systems

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F11%3A86084593" target="_blank" >RIV/61989100:27240/11:86084593 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Using SVM and clustering algorithms in IDS systems
Original language description
Intrusion Detection System (IDS) is a system, that monitors network traffic and tries to detect suspicious activity. In this paper we discuss the possibilities of application of clustering algorithms and Support Vector Machines (SVM) for use in the IDS.There we used K-means, FarthestFirst and COBWEB algorithms as clustering algorithms and SVM as classification SVM of type 1, known too as C-SVM. By appropriate choosing of kernel and SVM parameters we achieved improvements in detection of intrusion to system. Finally, we experimentally verified the efficiency of applied algorithms in IDS.
Czech name
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Czech description
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Project
<a href="/en/project/GA205%2F09%2F1079" target="_blank" >GA205/09/1079: Methods of Artificial Inteligence in GIS</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
DATESO 2011 : databases, texts, specifications, and objects : proceedings of the Dateso 2011 Workshop
ISBN
978-80-248-2391-1
ISSN
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e-ISSN
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Number of pages
12
Pages from-to
108-119
Publisher name
Vysoká škola báňská - Technická univerzita, Fakulta elektrotechniky a informatiky, Katedra informatiky
Place of publication
Ostrava
Event location
Písek
Event date
Apr 20, 2011
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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