Survey of Data Mining Techniques for Intrusion Detection Systems

Aditya Nur Cahyo, E. Winarko, Aina Musdholifah
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引用次数: 2

Abstract

Nowadays, the number of cyber-attacks is increasing; therefore, it is important for companies or organizations to secure their networks. Intrusion Detection System (IDS) is one of the core components used to secure networks. IDS's role is to detect an attack or attempted attack. The security tools are growing rapidly, along with the increasing number and variety of attacks carried out. The same with the development of IDS, a lot of research has been done to improve the ability of IDS to detect an attack. Many studies have used data mining techniques on IDS. This paper aims to conduct a comprehensive survey on the use of data mining techniques on IDS in the last five years. In this survey, we category the techniques used into several categories, and discuss each category in detail.
入侵检测系统数据挖掘技术综述
如今,网络攻击的数量正在增加;因此,对于公司或组织来说,保护他们的网络是非常重要的。入侵检测系统(IDS)是保障网络安全的核心部件之一。IDS的作用是检测攻击或企图攻击。随着攻击的数量和种类的增加,安全工具也在迅速发展。随着入侵检测系统的发展,人们也做了大量的研究来提高入侵检测系统检测攻击的能力。许多研究在IDS上使用了数据挖掘技术。本文旨在对近五年来数据挖掘技术在IDS中的应用进行全面调查。在本调查中,我们将所使用的技术分为几类,并详细讨论每一类。
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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