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Reseach Article

Cyber-Attack Classification using Improved Ensemble Technique based on Support Vector Machine and Neural Network

by Bhavna Dharamkar, Rajni Ranjan Singh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 103 - Number 11
Year of Publication: 2014
Authors: Bhavna Dharamkar, Rajni Ranjan Singh
10.5120/18115-9346

Bhavna Dharamkar, Rajni Ranjan Singh . Cyber-Attack Classification using Improved Ensemble Technique based on Support Vector Machine and Neural Network. International Journal of Computer Applications. 103, 11 ( October 2014), 1-7. DOI=10.5120/18115-9346

@article{ 10.5120/18115-9346,
author = { Bhavna Dharamkar, Rajni Ranjan Singh },
title = { Cyber-Attack Classification using Improved Ensemble Technique based on Support Vector Machine and Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 103 },
number = { 11 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume103/number11/18115-9346/ },
doi = { 10.5120/18115-9346 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:34:14.940992+05:30
%A Bhavna Dharamkar
%A Rajni Ranjan Singh
%T Cyber-Attack Classification using Improved Ensemble Technique based on Support Vector Machine and Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 103
%N 11
%P 1-7
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cyber-attack classification and detection process is based on the fact that intrusive activities are different from normal system activities . Its detection is a very complex process in network security. In current network security scenario various types of cyber-attack family exist, some are known family and some are unknown one . The detection of known attack is not very difficult it generally uses either signature base approach or rule based approach, but to find out the unknown one is a challenging task. Intrusion detection is a process for this . One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. This paper addresses using of an ensemble classification methods for intrusion detection. The paper proposes a cascaded support vector machine classifier or an improved ensemble classifier using multiple kernel function. The multiple kernel is Gaussian in nature. The graph based /neural network technique used for feature collection of different types of cyber-attack data. The proposed algorithm is very efficient in comparison of pervious method.

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Index Terms

Computer Science
Information Sciences

Keywords

SVM Gaussian hyper plane Euclidean distance