遗传算法结合支持向量机构建入侵检测系统

International Conference on Advances in Computing, Communications and Informatics Pub Date : 2012-08-03 DOI:10.1145/2345396.2345489

S. Saha, A. Sairam, A. Yadav, Asif Ekbal

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引用次数: 17

摘要

本文开发了一种基于机器学习的入侵检测系统(IDS)。我们采用遗传算法(GA)和支持向量机(SVM)来自动确定合适的特征集。然后将这个想法发展成一个功能齐全的IDS。给出了在基准KDD CUP 99数据集上测试IDS的实验。结果显示出令人鼓舞的表现，为进一步的研究开辟了道路。

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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Genetic algorithm combined with support vector machine for building an intrusion detection system

In this paper, we develop an intrusion detection system (IDS) based on machine learning. We employ genetic algorithm (GA) along with Support Vector Machine (SVM) for automatically determining the appropriate set of features. The idea is then developed into a fully functional IDS. Experiments of testing the IDS on the benchmark KDD CUP 99 datasets are presented. Results show encouraging performance that opens a avenue for further research.

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International Conference on Advances in Computing, Communications and Informatics

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