DoS Attack Detect Framework Based on Multivariate Correlation Analysis

Computer Engineering

A Denial-of-Service (DoS) attack is an intrusive attempt, which aims to force a designated resource to be unavailable to its intended users. This attack is launched either by vulnerabilities of a victim (e.g., a host, a router, or an entire network) or by flooding a victim with large volume of useless network traffic. Since 1990s, DoS attacks have emerged as a type of the most severe network intrusive behaviours and have posed serious threats to the infrastructures of computer networks and various network-based services. In this paper describe Multivariate Correlation analysis (MCA) .It is an intelligent and effective solution for DoS attack detection that use for accurate network traffic characterization by extracting the geometrical correlations between network traffic features. MCA based DoS attack detection system employs the principle of anomaly-based detection in attack recognition. Multivariate Correlation Analysis approaches are proposed based on two techniques, namely Euclidean distance and triangle area. These two proposed MCA approaches provide accurate description for network traffic records

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