Intrusion Detection Techniques : A Review

Authors

  • Sandip Hingane   M. Tech Scholar, Department of CSE, NIIST Bhopal Madhya Pradesh, India
  • Dr. Umesh Kumar Lilhore   Head, Department of CSE, NIIST Bhopal Madhya Pradesh, India

Keywords:

Intrusion Detection, Network-Based, Host-Based, Data Mining, Machine Learning.

Abstract

Now, these days Internet technology is widely used everywhere. Most of the Internet-based applications are publically available for all the users. This public nature of Internet-based applications increases security threats. So security of user data and information is an important issue and need high attention in the research area. An intrusion detection system is designed for detection and classification of various attacks. It classifies attacks into normal and abnormal classes. Intrusion detection systems are based on either host based or network based. Various data mining and machine learning methods are widely used by ID systems. In this paper, we are presenting a review of various intrusion detection methods.

References

  1. Amreen Sultana, M.A.Jabbar, "Intelligent Network Intrusion Detection System using Data Mining Techniques", IEEE 2nd International Conference on Applied and Theoretical Computing and Communication Technology (ICAC), July 2016, pp 329-334.
  2. M A Jabbar a, Rajanikanth Aluvalub, Sai Satyanarayana Reddy S," RFAODE: A Novel Ensemble Intrusion Detection System", ELSEVIER 7th International Conference on Advances in Computing & Communications, ICACC-2017, 22-24 August 2017, Cochin, India, pp 226-234.
  3. Levent Koc and Alan D. Carswell," Application of an AODE Based Classifier to Detect DOS Attacks", IJCSNS International Journal of Computer Science and Network Security, VOL.15 No.2, February 2015, pp 24-29.
  4. Adel Ammar," Adel AmmarA Decision Tree Classifier for Intrusion Detection Priority Tagging", Journal of Computer and Communications, 3, March 2015, pp 52-58.
  5. Sean T Miller, Curtis Busby-Earle, "Multi-Perspective Machine Learning a Classifier Ensemble Method for Intrusion Detection", ICMLSC '17 Proceedings of the 2017 International Conference on Machine Learning and Soft Computing, Jan 2017, pp 7-12.
  6. Sharmila Kishor Wagh, Vinod K. Pachghare, Satish R. Kolhe, "Survey on Intrusion Detection System using Machine Learning Techniques", International Journal of Computer Applications (0975- 8887) Volume 78, No. 16, September 2013, pp 30-38.
  7. Roshani Gaidhane, Prof. C. Vaidya, Dr. M. Raghuwanshi," A Survey: Learning Techniques for Intrusion Detection System (IDS)", International Journal of Advance Foundation and Research in Computer (IJAFRC) Volume 1, Issue 2, Feb 2014, pp 21-29.
  8. Sejal K. Patel, Umang H. Mehta, Urmi M. Patel, Dhruv H. Bhagat,"A Technical Review on Intrusion Detection System", International Journal of Computer Science & Engineering Technology (IJCSET), Vol. 6 No. 01 Jan 2015, pp 17-25.
  9. AbdullaAminAburomman,"Surveyoflearningmethodsinintrusiondetection system", 2016 International Conference on Advances in Electrical, Electronic and System Engineering, 14-16 Nov 2016, pp 362-366.
  10. Vipin Das, Vijaya Pathak, Sattvik Sharma, Sreevathsan, MVVNS.Srikanth, Gireesh Kumar T", Network intrusion detection system based on machine learning algorithms", International Journal of Computer Science & Information Technology (IJCSIT), Vol. 2, No 6, December 2010, pp 138-152.
  11. Nutan Farah Haq, Musharrat Rafni," Application of Machine Learning Approaches in Intrusion Detection System: A Survey", (IJARAI) International Journal of Advanced Research in Artificial Intelligence, Vol. 4, 2015, pp 9-19.
  12. Trupti Phutane, Apashabi Pathan," A Survey of Intrusion Detection System Using Different Data Mining Techniques", International Journal of Innovative Research in Computer and Communication Engineering Vol. 2, Issue 11, November 2014, pp 6801-6808.
  13. Chirag Modi, Dhiren Patel a, Bhavesh Borisaniya a, Hiren Patel b," A survey of intrusion detection techniques in Cloud", ELSEVIER Journal of Network and Computer Applications, June 2012, pp 42-57.
  14. Yanjie Zhao," Network Intrusion Detection System Model Based on Data Mining", IEEE SNPD 2016, May 30-June 1, 2016, Shanghai, China, pp 206-212.
  15. M.A. Jabbar, B.L. Deekshatulu, Priti Chandra, "Computational intelligence techniques for early diagnosis of heart disease", ICETECH, IEEE 2015, pp 127-133.
  16. C.Ellcan, "Results of the KDD CUP 99 classifier learning "ACM SIG-KDD, Explorations newsletter, Feb-2000, 119-128.
  17. Theodoros Lappas and Konstantinos Pelechrinis," Data Mining Techniques for (Network) Intrusion Detection Systems", International Journal of Computer and Telecommunications Networking, Vol. 64, Issue 7, June 2015, pp: 206-219.
  18. Krishna Kant Tiwari, Susheel Tiwari, Sriram Yadav, Intrusion Detection Using Data Mining Techniques, IJACT, Nov 2016, pp21-27.
  19. Kapil Wankhade, Sadia Patka," An Efficient Approach for Intrusion Detection Using Data Mining Methods", IEEE 2013 International Conference on Advances in Computing, Communications, and Informatics (ICACCI), June 2013, pp 1615-1618.
  20. Arif Jamal Malik, Waseem Shahzad, Farrukh Aslam Khan, "Network ID using hybrid binary PSO and RF algorithm", Security and Communication Network, March 2012, pp 158-165.
  21. P. Natesan, P. Balasubramanie, "Multi-Stage Filter Using Enhanced Ad boost for Network Intrusion Detection", International Journal of Network Security & Its Applications (IJNSA), Vol. No. 3, May 2012, pp 226-239.
  22. Preeti Agarwal, Sudhir Kumar Sharma, "Analysis of KDD Dataset Attributes Class wise For Intrusion Detection". 3rd International Conference on Recent Trends in Computing 2015 (ICRTC-2015), pp 117-124.

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

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Published

2018-02-28

Issue

Volume 3, Issue 1, January-February-2018

Section

Research Articles

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

How to Cite

[1]
Sandip Hingane , Dr. Umesh Kumar Lilhore , " Intrusion Detection Techniques : A Review, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.129-135, January-February-2018.