Analyse Honey Pot Traffics to Detect DoS Attacks Using Support Vector Machine

Authors

  • C. Naveena  M.Phil Research Scholar, Department of Computer Science, Sankara College of Science and Commerce, Coimbatore, Tamil Nadu, India
  • R. Sasikala  Assistant Professor, Department of Computer Science, Sankara College of Science and Commerce, Coimbatore, Tamil Nadu, India

Keywords:

Honey pot, Dos, Data mining, SVM.

Abstract

Honeypots are physical or virtual machines successfully used as intrusion detection tools to detect worm-infected hosts. Denial of service (DoS) attack consumes the resources of a remote client or network itself, there by denying or degrading the service to the legitimate users. In this paper, we present a system that helps in the detection DoS attacks using the data mining framework. We have used support vector machine classifier to identify the honey pot traffic into normal and DoS attack.

References

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

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Published

2017-12-31

Issue

Volume 2, Issue 6, November-December-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]
C. Naveena, R. Sasikala, " Analyse Honey Pot Traffics to Detect DoS Attacks Using Support Vector Machine, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 6, pp.326-329, November-December-2017.