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An Efficient Way of Detecting Denial-Of-Service Attack Using Multivariate Correlation Analysis

S.Gomathi

Interconnected systems, such as Web servers, database servers, cloud computing servers etc, are now under threads from network attackers. As one of most common attack is Denial of Service (DoS) these attacks cause serious impact on computing systems. The shared nature of the medium in wireless networks makes it easy for an adversary to launch a Wireless Denial of Service (WDoS) attack. To give a simple example, a malicious node can continually transmit a radio signal in order to block any legitimate access to the medium and/or interfere with reception. This act is called jamming and the malicious nodes are referred to as jammers. Jamming techniques vary from simple ones based on the continual transmission of interference signals, to more sophisticated attacks that aim at exploiting vulnerabilities of the particular protocol used. DoS attack detection system that uses Multivariate Correlation Analysis (MCA) for accurate network traffic characterization by extracting the geometrical correlations between network traffic features. Our MCAbased DoS attack detection system employs the principle of anomaly-based detection in attack recognition. This makes our solution capable of detecting known and unknown DoS attacks effectively by learning the patterns of legitimate network traffic only.