Network-based intrusion detection using Adaboost algorithm

被引：0

作者：

Hu, W ^{[1
]}

Hu, WM ^{[1
]}

机构：

[1] Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100864, Peoples R China

来源：

2005 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE, PROCEEDINGS | 2005年

关键词：

intrusion detection; network-based IDS; AdaBoost; computational complexity;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

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.

引用

页码：712 / 717

页数：6

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