A Survey on Intrusion Detection Systems and Classification Techniques

Authors(2) :-Prof. Javed Akhtar Khan, Nitesh Jain

Today it is very important to provide a high level security to protect highly sensitive and private information. Intrusion Detection System is an essential technology in Network Security. Nowadays researchers have interested on intrusion detection system using Data mining techniques as an artful skill. IDS is a software or hardware device that deals with attacks by collecting information from a variety of system and network sources, then analyzing symptoms of security problems. This paper includes an overview of intrusion detection systems and introduces the reader to some fundamental concepts of IDS methodology. We also discuss the primary intrusion detection techniques. In this paper, we emphasizes data mining algorithms to implement IDS such as Support Vector Machine, Kernelized support vector machine, Extreme Learning Machine and Kernelized Extreme Learning Machine.

Authors and Affiliations

Prof. Javed Akhtar Khan
Department of Computer Science & Engineering, Takshshila Institute of Engineering & Technology, Jabalpur, Madhya Pradesh, India
Nitesh Jain
M. Tech Scholar, Takshshila institute of engineering & technology, Jabalpur, Madhya Pradesh, India

SVM, KELM, Intrusion Detection System, Data Mining and IDS, ELM, Classification Techniques for IDS, KSVM

  1. Defeng Wang, Yeung, D.S., and Tsang, E.C., "Weighted Mahalanobis Distance Kernels for Support Vector Machines", IEEE Transactions on Neural Networks, Vol. 18, No. 5, Pp. 1453-1462, 2007.
  2. Glenn M. Fung and O. L. Mangasarian, "Multicategory Proximal Support Vector Machine Classifiers", Springer Science and Business Media, Machine Learning, 59, 77–97, 2005.
  3. Guang-Bin Huang, Dian Hui Wang and Yuan Lan, "Extreme learning machines: a survey", Published: 25 May 2011_ Springer-Verlag, 2011.
  4. Hyeran Byun and Seong-Whan Lee, "Applications of Support Vector Machines for Pattern Recognition: A Survey", Springer-Verlag Berlin Heidelberg, 2002
  5. Jacob Victor, Dr. M Sreenivasa Rao and Dr. V. CH. Venkaiah, "Intrusion Detection Systems Analysis and Containment of False Positives Alerts", International Journal of Computer Applications (0975 – 8887), Volume 5– No.8, August 2010.
  6. Joseph,J.F.C., Bu-Sung Lee, Das,A., and Boon-Chong Seet, "Cross-Layer Detection of Sinking Behavior in Wireless Ad Hoc Networks Using SVM and FDA", IEEE Transactions on Dependable and Secure Computing, Vol. 8, No. 2, Pp. 233-245, 2011.
  7. Kyaw Thet Khaing, "Enhanced Features Ranking and Selection using Recursive Feature Elimination (RFE) and k-Nearest Neighbor Algorithms in Support Vector Machine for Intrusion Detection System", International Journal of Network and Mobile Technologies, Vol. 1,No. 1, Pp. 8-14, 2010.
  8. Manish Joshi, "Classification, Clustering and Intrusion Detection System", International Journal of Engineering Research and Applications (IJERA), ISSN: 2248-9622, pp.961-964, Vol. 2, Issue 2, Mar-Apr 2012.
  9. Mohammad Sazzadul Hoque, Md. Abdul Mukit and Md. Abu Naser Bikas, "An Implementation Of Intrusion Detection System Using Genetic Algorithm", International Journal of Network Security & Its Applications (IJNSA), Vol.4, No.2, March 2012.
  10. Rajesh and J. Siva Prakash, "Extreme Learning Machines - A Review and State-of-the-art", International Journal of Wisdom Based Computing, Vol. 1(1), 2011.
  11. Reema Patel, Amit Thakkar and Amit Ganatra, "A Survey and Comparative Analysis of Data Mining Techniques for Network Intrusion Detection Systems", International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-2, Issue-1, March 2012. 12Sandip Sonawane, Shailendra Pardeshi and Ganesh Prasad, "A survey on intrusion detection techniques", World Journal of Science and Technology, 2012.
  12. Wenke Lee and Salvatore J. Stolfo, "Data Mining Approaches for Intrusion Detection", Pp. 79–94 of the Proceedings, 7th USENIX Security Symposium, 1998.

Publication Details

Published in : Volume 2 | Issue 5 | September-October 2016
Date of Publication : 2016-10-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 202-208
Manuscript Number : IJSRSET162561
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Prof. Javed Akhtar Khan, Nitesh Jain , " A Survey on Intrusion Detection Systems and Classification Techniques, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 5, pp.202-208, September-October-2016. Citation Detection and Elimination     |     
Journal URL : https://ijsrset.com/IJSRSET162561

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