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

  1. S.Mukkamala,A.H.Sung,A.Abraham,Intrusion detection using an ensemble of intelligent paradigms, Journal of network and computer applications 28 (2) (2005) 167-182.
  2. S. Mukkamala, A. H. Sung, Significant feature selection using computational intelligent techniques for intrusion detection, in Advanced Methods for Knowledge Discovery from Complex Data, Springer, 2005, pp. 285-306.
  3. S. Chebrolu, A. Abraham, J. P.Thomas, Feature deduction andensemble design of intrusion detection systems, Computers &Security 24 (4) (2005) 295-307.
  4. Y. Chen, A. Abraham, B. Yang, Feature selection and classification flexible neural tree, Neurocomputing 70 (1) (2006) 305-313.
  5. S.-J. Horng, M.-Y. Su, Y.-H. Chen, T.-W. Kao, R.-J. Chen, J.-L.Lai, C.D.Perkasa, A novel intrusion detection system based on hierarchical clustering and support vector  machines, Expert systems with Applications 38 (1) (2011) 306-313.
  6. A. N. Toosi, M. Kahani, A new approach to intrusion detection based on an evolutionary soft computing model using  neuro-fuzzy classifiers, Computer communications 30 (10) (2007) 2201-2212.

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

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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, IInternational 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.