文章基本信息

标题：Using Learning Vector Quantization in IDS Alert Management System
本地全文：下载
作者：Mr. Amir Azimi Alasti Ahrabi ; Mr. Kaveh Feyzi ; Mr. Zahra Atashbar Orang 等
期刊名称：International Journal of Computer Science and Security (IJCSS)
电子版ISSN：1985-1553
出版年度：2012
卷号：6
期号：2
页码：128-134
出版社：Computer Science Journals
摘要：Intrusion detection system (IDS) is used to produce security alerts to discover attacks against protected network and/or computer systems. IDSs generate high amount of security alerts and analyzing these alert by a security expert are time consuming and error pron. IDS alert management system are used to manage generated alerts and classify true positive and false positives alert. This paper represents an IDS alert management system that uses learning vector quantization technique to classify generated alerts. Because of low classification time per each alert, the system also could be used in active alert management systems.
关键词：IDS; Alert Management; Learning Vector Quantization; Alert Classification; True Positive and False Positive Classification