A Survey on Intrusion Detection Systems

Authors

  • Shivendu Dubey  Gyan Ganga Institute of Technology & Science, Jabalpur, Madhya Pradesh, India
  • Neha Tripathi  Gyan Ganga Institute of Technology & Science, Jabalpur, Madhya Pradesh, India

Keywords:

Intrusion Detection, Anomaly-based Detection, Signature-based detection

Abstract

With the advent of anomaly based intrusion detection systems, many approaches and techniques have been developed to track novel attacks on the systems. Though anomaly based approaches are efficient, signature based detection is preferred for mainstream implementation of intrusion detection systems. As a variety of anomaly detection techniques were suggested, it is difficult to compare the strengths, weaknesses of these methods. The reason why industries don?t favor the anomaly based intrusion detection methods can be well understood by validating the efficiencies of the all the methods. To investigate this issue, the current state of the experiment practice in the field of anomaly based intrusion detection is reviewed and survey recent studies in this. This paper contains summarization study and identification of the drawbacks of formerly surveyed works.

References

  1. M. Bahrololum and M. Khaleghi, “Anomaly Intrusion Detection System Using Hierarchical Gaussian Mixture Model” IJCSNS International Journal of Computer Science and Network Security, VOL.8 No.8, August 2008
  2. Jiankun Hu and Xinghuo Yu, “A Simple and Efficient Hidden Markov Model Scheme for Host-Based Anomaly Intrusion Detection” IEEE Network Journal, Volume 23 Issue 1, January/February 2009
  3. R. Nakkeeran, T. Aruldoss Albert and R.Ezumalai, “Agent Based Efficient Anomaly Intrusion Detection System in Ad-hoc networks” IACSIT International Journal of Engineering and Technology Vol. 2, No.1, February, 2010
  4. Jiong Zhang and Mohammad Zulkernine, “Anomaly  Based Network Intrusion Detection with Unsupervised Outlier Detection” IEEE International Conference on Communications, 2006.
  5. Ahmed Awad E. Ahmed, and Issa Traore, “Anomaly Intrusion Detection based on Biometrics”, IEEE Workshop on Information Assurance 2005
  6. Vijay Bhuse, Ajay Gupta, “Anomaly Intrusion Detection  in  Wireless  Sensor  Networks”  ACM  Journal  of  High Speed Networks, 2006
  7. Hossein M. Shirazi,”Anomaly Intrusion Detection System Using Information Theory, K-NN and  KMC Algorithms”, Australian Journal of Basic and Applied Sciences, 3(3): 2581-2597, 2009
  8. Dayu Yang, Alexander Usynin, and J. Wesley Hines, “Anomaly-Based Intrusion Detection for SCADA Systems” IAEA Technical Meeting on Cyber Security of NPP I&C and Information systems, Idaho Fall, ID, Oct. 2006
  9. M.Thangavel, Dr. P.Thangaraj and K.Saravanan, “Defend against Anomaly Intrusion Detection using SWT Mechanism” IACSIT, 2010
  10. Miao Wang, Cheng Zhang and Jingjing, “Native API Based Windows Anomaly Intrusion Detection Method Using SVM” IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy  Computing, 2006
  11. Manikopoulos.C and Papavassiliou.S, “Network Intrusion and Fault Detection: A Statistical Anomaly Approach” IEEE Communications, 2002.
  12. Jeyanthi Hall, Michel Barbeau, Evangelos Kranakis, “Using Mobility Profiles for Anomaly-based Intrusion Detection in Mobile Networks” IEEE Conference, 2005.
  13. Hazem M. El-Bakry, Nikos MastorakisA, “Real-Time Intrusion Detection Algorithm for Network Security,WSEAS Transactions on communications, Issue 12, Volume 7, December 2008.
  14. Debar.H, Dacier.M and Wespi.A, “A Revised Taxonomy of Intrusion-Detection Systems” Annales des Telecommunications 55(7–8) (2000) 361–378
  15. Allen.J, Christie.A, Fithen.W, McHugh.J, Pickel.J, Stoner.E, “State of the practice of intrusion detection technologies” Technical Report CMU/SEI-99TR- 028, Carnegie-Mellon University - Software Engineering Institute (2000).
  16. Roesch.M, “Snort - Lightweight Intrusion Detection for Networks” 13th USENIX Conference on System Administration, USENIX Association (1999) 229–238
  17. Sourcefire: Snort Network Intrusion Detection System web site (1999) URL http://www.snort.org.
  18. Wang. K and Stolfo.S.J, “Anomalous Payload-Based Network Intrusion Detection” 7th Symposium on Recent Advances in Intrusion Detection, Volume 3224  of LNCS., Springer-Verlag (2004) 203–222
  19. Bolzoni.D, Zambon.E., Etalle.S, Hartel.P, “POSEIDON: a 2-tier Anomaly based Network Intrusion Detection System”IEEE International Workshop on Information Assurance, IEEE Computer Society Press (2006) 144– 156.
  20. B.Pfahringer, "Winning the KDD99 Classification Cup: Bagged Boosting," in SIGKDD Explorations, 2000.
  21. I. Levin, "KDD-99 Classifier Learning  Contest: LLSoft‟s Results Overview" SIGKDD Explorations, 2000.
  22. V. Miheev, Vopilov.A and Shabalin.I., "The MP13 Approach to the KDD‟99 Classifier Learning Contest" SIGKDD Explorations, 2000.

International Journal of Scientific Research in Science, Engineering and Technology

Downloads

Published

2015-12-25

Issue

Volume 1, Issue 6, November-December-2015

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

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

How to Cite

[1]
Shivendu Dubey, Neha Tripathi, " A Survey on Intrusion Detection Systems, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 6, pp.29-40, November-December-2015.