Classification of Attacks Using Support Vector Machine (SVM) on KDDCUP'99 IDS Database

被引：27

作者：

Kotpalliwar, Manjiri V. ^{[1
]}

Wajgi, Rakhi ^{[1
]}

机构：

[1] YCCE, Dept Comp Sci & Engn, Nagpur, Maharashtra, India

来源：

2015 FIFTH INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS AND NETWORK TECHNOLOGIES (CSNT2015) | 2015年

关键词：

SVM; Data Mining; KDDCUP'99 IDS database;

D O I：

10.1109/CSNT.2015.185

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Intrusion Detection System (IDS) is used to preserve the data integrity and confidentiality from attacks. In order to identify the type of attack in IDS, different methodologies like various data mining techniques exist. But some are very time consuming and laborious. Therefore we have proposed the usage of SVM (Support Vector Machine) for classification of attack from large amount of raw intrusion detection datasets on standard personal computers. SVM is a method which is used in data mining to extract predicted data. We have use KDDCUP' 99 IDS database for classification.

引用

页码：987 / 990

页数：4

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