Redundant and Irrelevant Feature Detection System using Online Feature Selection Algorithm

Authors(2) :-G. Supriya , Dr. A. Sureshbabu

Developing effective and adaptive security approaches in network has become more critical than ever before. Security techniques such as Intrusion detection system is highly recommended to provide security but such security defence systems facing decision making problems due to the presence of irrelevant and redundant feature. To handle this condition, online feature selection algorithm has been proposed in this paper. With the help of this proposed technique, intruder will be identified by classifying packets as anomaly and normal .

Authors and Affiliations

G. Supriya
M. Tech, Department of CSE, JNTUA College of Engineering Ananthapuramu, Andhra Pradesh, India
Dr. A. Sureshbabu
Associate Professor, Department of CSE, JNTUA College of Engineering, Ananthapuramu, Andhra Pradesh, India

Feature Selection, Intrusion detection, KDD Cup 99 Dataset.

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Publication Details

Published in : Volume 2 | Issue 4 | July-August 2017
Date of Publication : 2017-08-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 743-745
Manuscript Number : CSEIT11724111
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

G. Supriya , Dr. A. Sureshbabu, "Redundant and Irrelevant Feature Detection System using Online Feature Selection Algorithm", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 4, pp.743-745, July-August-2017.
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