Network Intrusion Detection Using Improved Genetic k-means Algorithm

被引：0
|
作者：
Sukumar, Anand J., V [1 ]
Pranav, I [1 ]
Neetish, M. M. [1 ]
Narayanan, Jayasree [1 ]
机构：
[1] Amrita Vishwa Vidyapeetham, Dept Comp Sci & Engn, Amritapuri, India
来源：
2018 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI) | 2018年
关键词：
Internet; Network Intrusion; Intrusion Detection; Intrusion Detection System; IGKM algorithm; k-means plus plus algorithm; KDD-99;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Internet is a widely used platform nowadays by people across the globe. This has led to the advancement in science and technology. Many surveys show that network intrusion has registered a consistent increase and lead to personal privacy theft and has become a major platform for attack in the recent years. Network intrusion is any unauthorized activity on a computer network. Hence there is a need to develop an effective intrusion detection system. In this paper we acquaint an intrusion detection system that uses improved genetic k-means algorithm(IGKM) to detect the type of intrusion. This paper also shows a comparison between an intrusion detection system that uses the k-means++ algorithm and an intrusion detection system that uses IGKM algorithm while using smaller subset of kdd-99 dataset with thousand instances and the KDD-99 dataset. The experiment shows that the intrusion detection that uses IGKM algorithm is more accurate when compared to k-means++ algorithm.
引用
收藏
页码：2441 / 2446
页数：6
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