一种基于决策树的入侵检测方法

2010 International Conference on E-Health Networking Digital Ecosystems and Technologies (EDT) Pub Date : 2010-04-17 DOI:10.1109/EDT.2010.5496597

Yongjin Liu, Na Li, Leina Shi, Fangping Li

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引用次数: 11

摘要

如何发现入侵行为是困扰入侵检测领域多年的问题。到目前为止，还没有一个很好的方法来解决这个问题，特别是在现实环境中。大多数方法在小数据集上是有效的，但当用于IDS的海量数据时，效果似乎不尽如人意。针对海量数据检测率低的问题，提出了一种基于决策树的新方法。

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An intrusion detection method based on decision tree

How to find the intrusion behaviors is a problem that troubled the intrusion detection field for years. Until now, there is not a good method to solve it, epically in a realistic context. Most methods are effective on small data sets, but when used to the massive data of IDS, the effectiveness seems to be unsatisfactory. In this paper, a new method based on decision tree is discussed to solve the problem of low detection rate of massive data.

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2010 International Conference on E-Health Networking Digital Ecosystems and Technologies (EDT)

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