DocumentCode
2449234
Title
Applied Research on Data Mining Algorithm in Network Intrusion Detection
Author
Xue, Ming ; Zhu, Changjun
Author_Institution
Changchun Inst. of Technol., Changchun, China
fYear
2009
fDate
25-26 April 2009
Firstpage
275
Lastpage
277
Abstract
Intrusion detection is one of network security area of technology main research directions. Data mining technology was applied to network intrusion detection system (NIDS), may automatically discover the new pattern from the massive network data, to reduce the workload of the manual compilation intrusion behavior patterns and normal behavior patterns. This article reviewed the current intrusion detection technology and the data mining technology briefly. Focus on data mining algorithm in anomaly detection and misuse detection of specific applications. For misuse detection, the main study the classification algorithm; for anomaly detection, the main study the pattern comparison and the cluster algorithm. In pattern comparison to analysis deeply the association rules and sequence rules . Finally, has analysed the difficulties which the current data mining algorithm in intrusion detection applications faced at present, and has indicated the next research direction.
Keywords
data mining; pattern classification; security of data; anomaly detection; association rules; classification algorithm; data mining algorithm; misuse detection; network intrusion detection system; network security; pattern discovery; sequence rules; Algorithm design and analysis; Association rules; Classification algorithms; Clustering algorithms; Data mining; Data security; Face detection; Intrusion detection; Manuals; Pattern analysis; classification; data mining; intrusion detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Artificial Intelligence, 2009. JCAI '09. International Joint Conference on
Conference_Location
Hainan Island
Print_ISBN
978-0-7695-3615-6
Type
conf
DOI
10.1109/JCAI.2009.25
Filename
5158993
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