Denial-Of-Service Attack Detection Based On Multivariate Correlation Analysis and Triangle Area Map Generation
Denial-Of-Service Attack Detection Based On Multivariate Correlation Analysis and Triangle Area Map Generation
复制标题
基于多元相关分析和三角区域图生成的拒绝服务攻击检测
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
A. Hingmire
中科院分区：
文献类型：
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作者：
Parag Heena Salim Shaikh;Ramesh Kadam;N. Pratik;Prathamesh Pramod Shinde;Ravindra Patil Prof;A. Hingmire
在计算机领域，拒绝服务（DoS）是一种试图使计算机或网络资源对其预期用户不可用的行为。DoS攻击通常包括暂时或无限期中断或暂停连接到Internet的主机的服务。DoS攻击的实施者通常针对托管在高配置Web服务器上的站点或服务，例如银行，信用卡支付网关，甚至根名称服务器。Web服务器、数据库服务器、云计算服务器等系统很容易受到网络黑客的攻击。拒绝服务（DoS）攻击对这些计算系统造成灾难性的影响。本文提出了一种利用多变量相关分析（MCA）技术检测拒绝服务攻击的检测系统。MCA技术通过提取网络流量特征之间的几何相关性，用于精确的网络流量表征。对于攻击识别，该系统采用基于异常的检测原理。该原理的使用使得通过仅学习合法网络流量的模式来有效地检测已知和未知的拒绝服务攻击变得更加容易。
: In computing, a denial-of-service (DoS) is an attempt to make a machine or network resource unavailable to its intended users. A DoS attack generally consists of efforts to temporarily or indefinitely interrupt or suspend services of a host connected to the Internet. Perpetrators of DoS attacks typically target sites or services hosted on high-profile web servers such as banks, credit card payment gateways, and even root name servers. Systems like Web servers, database servers, cloud computing servers etc. are very vulnerable to be attacked by network hackers. Denial-of-Service (DoS) attacks cause disastrous effects on these computing systems. In this paper, a detection system is proposed that detects DoS attacks by using the technique of Multivariate Correlation Analysis (MCA). The technique of MCA is used for accurate network traffic characterization by extracting the geometrical correlations between network traffic features. For attack recognition, proposed system uses the principle of anomaly-based detection. The use of this principle makes it easier for detecting known and unknown DoS attacks effectively by learning the patterns of legitimate network traffic only.