DocumentCode :
2186142
Title :
Network-based intrusion detection using Adaboost algorithm
Author :
Hu, Wei ; Hu, Weiming
Author_Institution :
Inst. of Autom., Chinese Acad. of Sci., China
fYear :
2005
fDate :
19-22 Sept. 2005
Firstpage :
712
Lastpage :
717
Abstract :
Intrusion detection on the Internet is a heated research field in computer science, where much work has been done during the past two decades. In this paper, we build a network-based intrusion detection system using Adaboost, a prevailing machine learning algorithm. The experiments demonstrate that our system can achieve an especially low false positive rate while keeping a preferable detection rate, and its computational complexity is extremely low, which is a very attractive property in practice.
Keywords :
Internet; computational complexity; learning (artificial intelligence); security of data; Adaboost algorithm; Internet; computational complexity; machine learning; network-based intrusion detection; Automation; Computational complexity; Data mining; IP networks; Internet; Intrusion detection; Laboratories; Machine learning algorithms; Pattern recognition; Support vector machines; AdaBoost; Computational complexity; Intrusion detection; Network-based IDS;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence, 2005. Proceedings. The 2005 IEEE/WIC/ACM International Conference on
Print_ISBN :
0-7695-2415-X
Type :
conf
DOI :
10.1109/WI.2005.107
Filename :
1517940
Link To Document :
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