Network-based intrusion detection using Adaboost algorithm

Wei Hu, Weiming Hu
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引用次数: 40

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.
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基于Adaboost算法的网络入侵检测
Internet上的入侵检测是计算机科学研究的一个热点,在过去的二十年里已经做了大量的工作。在本文中,我们使用Adaboost(一种流行的机器学习算法)构建了一个基于网络的入侵检测系统。实验表明,该系统在保持较好的检测率的同时,可以实现特别低的误报率,并且其计算复杂度极低,这在实际应用中是一个非常有吸引力的特性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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