Improved MCA Based DoS Attack Detection
Journal Title: International Journal of Science Engineering and Advance Technology - Year 2015, Vol 3, Issue 8
Abstract
A denial of service (DoS) attack is a malicious attempt to make a server or a network resource unavailable to users, usually by temporarily interrupting or suspending the services of a host connected to the Internet Interconnected systems, such as Web servers, database servers, cloud computing servers etc, are now under threads from network attackers. As one of most common and aggressive means, Denial-of-Service (DoS) attacks cause serious impact on these computing systems. In this paper, we present a 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 MCA-based DoS attack detection system employs the principle of anomalybased 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. Furthermore, a triangle-area-based technique is proposed to enhance and to speed up the process of MCA. The effectiveness of our proposed detection system is evaluated using KDD Cup 99 dataset, and the influences of both non-normalized data and normalized data on the performance of the proposed detection system are examined. The results show that our system outperforms two other previously developed state-of-the-art approaches in terms of detection accuracy.
Authors and Affiliations
Lakshmi Prasanna Kumar Relangi| M.Tech (IT), S.R.K.R.Engineering College, Bhimavaram, A.P., India, M. Krishna Satya Varma| Asst Professor, Dept. of Information Technology, S.R.K.R.Engineering College, Bhimavaram, A.P., India
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