Denial-of-service attack detection system

Supriya S. Thakare, P. Kaur
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引用次数: 7

Abstract

Use of online applications in day-to-day life is increasing. In parallel to this increase the threat to the security of these applications is also increasing. The security of these applications is breached by different cyber attacks. Denial-of-Service (DoS) is one such type of cyber attack. DoS makes the online application or the resources of the server unavailable to the intended users. For detecting these DoS attacks a detection system is proposed which can be used for detecting both known and unknown attacks. In the proposed system makes use of multivariate correlation analysis (MCA) technique which extracts the geometrical correlation between network traffic. This geometrical correlation is used for detecting DoS attack. Triangle area based technique to used enhance and speedup the MCA process. KDD cup 99 dataset is for examining the effectiveness of the proposed system. To increase the detection rate and to reduce the complexity of the proposed system a subset of features of the record is used. This subset is used in the whole detection process.
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拒绝服务攻击检测系统
在线应用程序在日常生活中的使用越来越多。与此同时,对这些应用程序的安全威胁也在不断增加。这些应用程序的安全性被不同的网络攻击所破坏。拒绝服务(DoS)就是这样一种网络攻击。DoS使在线应用程序或服务器的资源对预期用户不可用。为了检测这些DoS攻击,提出了一种可以同时检测已知和未知攻击的检测系统。该系统利用多元相关分析(MCA)技术提取网络流量之间的几何相关性。这种几何相关性用于检测DoS攻击。采用基于三角面积的技术,增强和加快了MCA过程。KDD cup 99数据集用于检查所提议系统的有效性。为了提高检测率并降低所提出系统的复杂性,使用了记录特征的子集。该子集用于整个检测过程。
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