A Data Mining Framework for Intrusion Detection System(IDS) using Bio-Inspired Algorithms

Authors

  • Qamar Rayees Khan  Baba Ghulam Shah Badshah University, Rajouri (J&K), India
  • Muheet Ahmed Butt  University of Kashmir, Srinagar, (J&K), India

Keywords:

Information System(IS), intrusion, Intrusion Detection Systems (IDS), biological inspired algorithms, Clustering, Mining and Classification.

Abstract

The information that acts a backbone for any organization is being managed by the sophisticated Information system (IS) is continuously under threat by the vurnabilities by the intrusion. There is always a need to have a better and proper security mechanism in place so that the effect of the intruders may be minimum and at the same time the information may not get compromised, This paper focus on the novel way of dealing the various Intrusions and proposed a model for the Intrusion Detection Systems (IDS). The use of biological inspired algorithms is used in the model for the optimization in terms of efficiency and accuracy. The proposed model comprises of three important phases (Clustering, Mining and classification) to deal with the threats that may occur in the information systems.

References

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

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Published

2016-12-30

Issue

Volume 1, Issue 3, November-December-2016

Section

Research Articles

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

How to Cite

[1]
Qamar Rayees Khan, Muheet Ahmed Butt, " A Data Mining Framework for Intrusion Detection System(IDS) using Bio-Inspired Algorithms , IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 1, Issue 3, pp.90-93, November-December-2016.