Network-based intrusion detection using Adaboost algorithm

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原文链接

NETL

外文摘要：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。

外文关键词：

Internetcomputational complexitylearning (artificial intelligence)security of dataAdaboost algorithmInternetcomputational complexitymachine learningnetwork-based intrusion detectionAdaBoostComputational complexityIntrusion detectionNetwork-ba

作者：

Wei Hu、Weiming Hu

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作者单位：

Inst. of Autom., Chinese Acad. of Sci., China

会议母体文献：

Web Intelligence, 2005. Proceedings. The 2005 IEEE/WIC/ACM International Conference on

页码：

P.712-717

DOI：

10.1109/WI.2005.107