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Denial-of-Service attack is an attempt to make network resources or machine unavailable to its intended users. It can temporarily or indefinitely interrupt or suspend the services of a host connected to the Internet. For the Detection of denial of service attack (DoS) various detection systems are developed. The existing system is based on sophisticated anomaly based system for detecting DoS attacks. But there is a problems occurs in this paper is that it reduces the performance of detecting the denial of service attack also it requires more time for the execution. This proposed system is developed to overcome these problems. To extract the features use SIFT it reduces the time when compared to the existing feature extraction method. The traffic records are trained as attack and non attack or the network traffic records changes the records into the respective images using Multivariate correlation analysis. Network traffic records images are used for the proposed denial of service attack detection system that is developed based on a dissimilarity measure Earth Movers Distance embedded with three dimensional reduction method. By using this method it can also detect the unknown Denial of Service attack. It efficiently measure the distance between trained records and new records. It increases the performance of detection of Denial of service attack and also requires only less time for the computation.

Detection of Denial of Service Attack Based on EMD Embedded with 3D Reduction Method