Genetic Algorithm Combined with Support Vector Machine for Building an Intrusion Detection System

被引：0
|
作者：
Saha, Sriparna [1 ]
Sairam, Ashok Singh [1 ]
Ekbal, Asif [1 ]
Yadav, Amulya [1 ]
机构：
[1] IIT Patna, Dept CSE, Patna, Bihar, India
来源：
PROCEEDINGS OF THE 2012 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI'12) | 2012年
关键词：
Genetic Algorithms; Support Vector Machines; Feature Selection; Intrusion Detection System;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：566 / 572
页数：7
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