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
Link To Document :
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