detecting denial of service attack using multivariate correlation analysis
P Chitra,P Pooja,V Vijayalakshmi,S Divya
Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology
ISSN: 2321-3337 Impact Factor:1.521 Volume:2 Issue:1 Year: 08 February,2014 Pages:13-17
Abstract
In computing, a denial-of-service (DoS) or distributed denial-of-service (DDoS) attack is an attempt to make a machine or network resource unavailable to its intended users. DOS attack reduces the efficiency of the server, inorder to increase the efficiency of the server it is necessary to detect the dos attacks. Hence MULTIVARIATE CORRELATION ANALYSIS is used, this approach employs triangle area for extracting the correlation information between the ip addresses. Based on the extracted information the denial of service attack is detected and the response to the particular ip address is blocked, thus increasing the efficiency. Our proposed system is evaluated using KDD Cup 99 data set, and the influence of data on the performance of the proposed system is examined.
Kewords
MULTIVARIATE CORRELATION ANALYSIS
Reference
[1] V. Paxson, “Bro: A System for Detecting Network Intruders in Realtime,” Computer Networks, vol. 31, pp. 2435-2463, 1999 [2] P. Garca-Teodoro, J. Daz-Verdejo, G. Maci-Fernndez, and E. Vzquez, “Anomaly-based Network Intrusion Detection: Techniques, Systems and Challenges,” Computers & Security, vol. 28, pp. 18-28, 2009. [3]. AdaBoost-Based Algorithm for Network Intrusion Detection Weiming Hu, Senior Member, IEEE, Wei Hu, and Steve Maybank, Senior Member, IEEE. [4]. Traffic flooding attack detection with SNMP MIB using SVMq Jaehak Yu, Hansung Lee, Myung-Sup Kim *, Daihee Park Department of Computer and Information Science, Korea University, Yeongi-Gun, Republic of Korea [5]. Parametric Methods for Anomaly Detection in Aggregate Traffic Gautam Thatte, Student Member, IEEE, Urbashi Mitra, Fellow, IEEE, and John Heidemann, Senior Member, IEEE. [6]. A System for Denial-of-Service Attack Detection Based on Multivariate Correlation Analysis Zhiyuan Tan, Aruna Jamdagni, Xiangjian He‡, Senior Member, IEEE, Priyadarsi Nanda, Member, IEEE, and Ren Ping Liu, Member, IEEE.
