CASIA OpenIR  > 09年以前成果
AdaBoost-based algorithm for network intrusion detection
Hu, Weiming1; Hu, Wei1; Maybank, Steve2
Source PublicationIEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
2008-04-01
Volume38Issue:2Pages:577-583
SubtypeArticle
AbstractNetwork intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. It is an indispensable part of the information security system. Due to the variety of network behaviors and the rapid development of attack fashions, it is necessary to develop fast machine-learning-based intrusion detection algorithms with high detection rates and low false-alarm rates. In this correspondence, we propose an intrusion detection algorithm based on the AdaBoost algorithm. In the algorithm, decision stumps are used as weak classifiers. The decision rules are provided for both categorical and continuous features. By combining the weak classifiers for continuous features and the weak classifiers for categorical features into a strong classifier, the relations between these two different types of features are handled naturally, without any forced conversions between continuous and categorical features. Adaptable initial weights and a simple strategy for avoiding overfitting are adopted to improve the performance of the algorithm. Experimental results show that our algorithm has low computational complexity and error rates, as compared with algorithms of higher computational complexity, as tested on the benchmark sample data.
KeywordAdaboost Computational Complexity Detection Rate False-alarm Rate Intrusion Detection
WOS HeadingsScience & Technology ; Technology
WOS KeywordANOMALY DETECTION ; NEURAL-NETWORKS ; MODEL ; ENSEMBLE ; BEHAVIOR
Indexed BySCI
Language英语
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000254029400029
Citation statistics
Cited Times:103[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9640
Collection09年以前成果
Affiliation1.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100080, Peoples R China
2.Univ London Birkbeck Coll, Sch Comp Sci & Informat, London WC1E 7HX, England
Recommended Citation
GB/T 7714
Hu, Weiming,Hu, Wei,Maybank, Steve. AdaBoost-based algorithm for network intrusion detection[J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS,2008,38(2):577-583.
APA Hu, Weiming,Hu, Wei,&Maybank, Steve.(2008).AdaBoost-based algorithm for network intrusion detection.IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS,38(2),577-583.
MLA Hu, Weiming,et al."AdaBoost-based algorithm for network intrusion detection".IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS 38.2(2008):577-583.
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