A Network Intrusion Detection Method Using Dempster-Shafer Theory
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12510%2F09%3A00011069" target="_blank" >RIV/60076658:12510/09:00011069 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
A Network Intrusion Detection Method Using Dempster-Shafer Theory
Original language description
An intrusion detection system (IDS) detects unauthorized manipulations of computer systems. Operation as feature reduction (including feature extraction and feature selection) plays an important role in the sense of improving classification performance and reducing the computational complexity of intrusion detection system. Feature reduction is even more important at online detection when less computational power and fast real time delivery compared with offline detection is needed. In this paper, Dempster Shafer theory based on KNN analysis approach is applied to feature extraction in online network intrusion detection problem. We used the KDD Cup 99 data. It has been shown that the Dempster-Shafer KNN classifier will result in higher classification accuracy in comparison with other two KNN classifiers.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Technical Computing Prague 2009
ISBN
978-80-7080-733-0
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
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Publisher name
Humusoft, s.r.o.
Place of publication
Praha
Event location
Praha
Event date
Nov 19, 2009
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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