Redundant and Irrelevant Feature Detection System using Online Feature Selection Algorithm

Authors

  • 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

Keywords:

Feature Selection, Intrusion detection, KDD Cup 99 Dataset.

Abstract

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 .

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2017-08-31

Issue

Volume 2, Issue 4, July-August-2017

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
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.