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Reseach Article

Intrusion Detection System based on Fuzzy C Means Clusteringand Probabilistic Neural Network

by Rachna Kulhare, Divakar Singh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 74 - Number 2
Year of Publication: 2013
Authors: Rachna Kulhare, Divakar Singh
10.5120/12860-9725

Rachna Kulhare, Divakar Singh . Intrusion Detection System based on Fuzzy C Means Clusteringand Probabilistic Neural Network. International Journal of Computer Applications. 74, 2 ( July 2013), 30-33. DOI=10.5120/12860-9725

@article{ 10.5120/12860-9725,
author = { Rachna Kulhare, Divakar Singh },
title = { Intrusion Detection System based on Fuzzy C Means Clusteringand Probabilistic Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 74 },
number = { 2 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 30-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume74/number2/12860-9725/ },
doi = { 10.5120/12860-9725 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:41:11.702215+05:30
%A Rachna Kulhare
%A Divakar Singh
%T Intrusion Detection System based on Fuzzy C Means Clusteringand Probabilistic Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 74
%N 2
%P 30-33
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Security is always an important issue especially in the case of computer network which is used to transfer personal/confidential information's, ecommerce and media sharing. Since the network is closely related to operating its conditions hence a careful observation & analysis of network characteristics could describe the state of the network such as network is under specific attack or operating normally. This paper presents an intrusion detection system based on fuzzy C-means clustering and probabilistic neural network which not only reduces the training time but also increases the detection accuracy. The proposed system is tested using KDD99 dataset and the simulation results shows that by selecting effective characteristics and proper training the detection accuracy rate up to 99% is achievable.

References
  1. Bing Wu, Jianmin Chen, Jie Wu and MihaelaCardei,"A Survey of Attacks and Countermeasures in Mobile Ad Hoc Networks", wireless/mobile network security,2006 Springer.
  2. Abhay Kumar Rai, Rajiv RanjanTewari and Saurabh Kant Upadhyay,"Different Types of Attacks on Integrated,MANET,InternetCommunication",Internatioal Journal of Computer Science and Security (IJCSS),Aug. 2010.
  3. KarimKonate and Gaye Abdourahime "Attacks Analysis in mobile ad hoc networks: Modeling and Simulation", Second International Conference on Intelligent Systems, Modelling and Simulation, 2011 IEEE.
  4. Farah Jemili, MontaceurZaghdoud and Mohamed Ben Ahmed,"A Framework for an Adaptive Intrusion Detection System using Bayesian Network", 2007 IEEE.
  5. Jingbo Yuan, Haixiao Li, Shunli Ding and Limin Cao "Intrusion Detection Model based on Improved Support Vector Machine", Third International Symposium on Intelligent Information Technology and Security Informatics, 2010 IEEE.
  6. Z. Muda, W. Yassin, M. N. Sulaiman and N. I. Udzir,"Intrusion Detection based on K-Means Clustering and OneR Classification", 2011 IEEE.
  7. http://link. springer. com/chapter/10. 1007%2F978-3-642-14400-4_50?LI=true#.
  8. http://www. personal. reading. ac. uk/~sis01xh/teaching/CY2D2/Pattern3. pdf
  9. http://voyagememoirs. com/pharmine/2008/06/22/probabilistic-neural-network-pnn/
  10. S. Nascimento, B. Mirkin and F. MouraPires "A Fuzzy Clustering Model of Data and Fuzzy c-Means", Fuzzy Systems, the Ninth IEEE International Conference on May,2000.
  11. Zhou Mingqiang and Huang Hui, Wang Qian,"A Graph-based Clustering Algorithm for Anomaly Intrusion Detection", The 7th International Conference on Computer Science & Education , July 2012. Melbourne, Australia.
  12. Sanjay Kumar Sharmai, PankajPande, Susheel Kumar Tiwari and Mahendra Singh Sisodia "An Improved Network Intrusion Detection Technique based on k-Means Clustering via NaIve Bayes Classificatio", IEEE-International Conference On Advances In Engineering, Science and Management March , 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Network Security Neural Network Intrusion Detection System Fuzzy C-Means Clustering KDD99 dataset