A Study on Intrusion Detection System using Clustering Techniques

Authors

  • Gaurav Kumar Das Computer Science & Engineering Kautilya Institute Of Technology & Engineering , Jaipur, India
  • Dr. Vijay Kumar Computer Science & Engineering Kautilya Institute Of Technology & Engineering , Jaipur, India

Keywords:

K – Means Clustering;SVM Classifier; Intrusion Detection System; RBF Kernel;

Abstract

The motivation behind this paper is to acquaint the client with to intrusion detection systems and give a profound comprehension of some complex methodology for intrusion detection. Intrusion Detection is a critical part of foundation security systems. Certain the collective complexities of today’s network environments, progressively hosts are becoming susceptible to attacks and hence it is significant to look at organized, efficient and computerizedmethods for Intrusion Detection. At this point, we discuss particular data mining clustering methods i.e. K- mean and K-medoids. We also express RBF kernel with the SVM classifier

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Published

2018-08-22

How to Cite

Das, G. K., & Kumar, D. V. . (2018). A Study on Intrusion Detection System using Clustering Techniques. International Journal of Technical Innovation in Modern Engineering & Science, 4(8), 458–463. Retrieved from https://ijtimes.com/index.php/ijtimes/article/view/800