DoS attacks prevention using IDS and data mining

2016 International Conference on Accessibility to Digital World, ICADW 2016 - Proceedings

Volumn , Issue , 2016, Pages 87-92

  Keshri, Anand ^a   Singh, Sukhpal ^a   Agarwal, Mayank ^a   Nandiy, Sunit Kumar ^b  

^a INDIAN INSTITUTE OF TECHNOLOGY GUWAHATI   (India)

^b NATIONAL INSTITUTE OF TECHNOLOGY   (India)

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING; NETWORK SECURITY; PERSONAL COMPUTING; STATISTICAL TESTS;

BUSINESS COMPANIES; DATA MINING ALGORITHM; DENIAL OF SERVICE; DOMAIN NAME SERVERS; LEGITIMATE USERS; NETWORK TRAFFIC; NSL-KDD DATASET; UNKNOWN ATTACKS;

DENIAL-OF-SERVICE ATTACK;

EID: 85027014073     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICADW.2016.7942518     Document Type: Conference Paper

References (16)

1. R. Subramani and R. Sridhar, "Denial of Service attacks and mitigation techniques: Real time implementation with detailed analysis, " manuscript, School of Computer Science and Electronic Engineering, University of Esse, 2011.
2. Rajkumar and M. J. Nene, "A Survey on Latest DoS Attacks: Classification and Defense Mechanisms, " IJIRCCE, vol. 1, 2013.
3. C. Douligeris and A. Mitrokotsa, "DDoS attacks and defense mechanisms: classification and state-of-The-Art, " Computer Networks, vol. 44, no. 5, pp. 643-666, 2004.
4. P. Ferguson, "Network ingress filtering: Defeating denial of service attacks which employ ip source address spoofing, " 2000.
5. T. M. Gil and M. Poletto, "Multops: A data-structure for bandwidth attack detection, " in USENIX Security Symposium, 2001, pp. 23-38.
6. S. Abdelsayed, D. Glimsholt, C. Leckie, S. Ryan, and S. Shami, "An efficient filter for denial-of-service bandwidth attacks, " in Global Telecommunications Conference, 2003. GLOBECOM'03. IEEE, vol. 3. IEEE, 2003, pp. 1353-1357.
7. D. E. Denning, "An intrusion-detection model, " Software Engineering, IEEE Transactions on, no. 2, pp. 222-232, 1987.
8. A. Chauhan, G. Mishra, and G. Kumar, Survey on data mining techniques in intrusion detection. Lap Lambert Academic Publ, 2012.
9. W. Lee, S. J. Stolfo, P. K. Chan, E. Eskin, W. Fan, M. Miller, S. Hershkop, and J. Zhang, "Real time data mining-based intrusion detection, " in DARPA Information Survivability Conference & Exposition II, 2001. DISCEX'01. Proceedings, vol. 1. IEEE, 2001, pp. 89-100.
10. K. Ilgun, "USTAT: A real-Time intrusion detection system for UNIX, " in Research in Security and Privacy, 1993. Proceedings., 1993 IEEE Computer Society Symposium on. IEEE, 1993, pp. 16-28.
11. S. Mukkamala, G. Janoski, and A. Sung, "Intrusion detection using neural networks and support vector machines, " in Neural Networks, 2002. IJCNN'02. Proceedings of the 2002 International Joint Conference on, vol. 2. IEEE, 2002, pp. 1702-1707.
12. M. Tavallaee, E. Bagheri, W. Lu, and A.-A. Ghorbani, "A detailed analysis of the KDD CUP 99 data set, " in Proceedings of the Second IEEE Symposium on Computational Intelligence for Security and Defence Applications 2009, 2009.
13. F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay, "Scikit-learn: Machine Learning in Python, " Journal of Machine Learning Research, vol. 12, pp. 2825-2830, 2011.
14. Scikit-learn.org, "1.9. Naive Bayes scikit-learn 0.17.1 documentation, " 2016, [Online; accessed 27-March-2016]. [Online]. Available: http://scikit-learn.org/stable/modules/naivebayes.html.
15. G. Münz, S. Li, and G. Carle, "Traffic anomaly detection using k-means clustering, " in GI/ITG Workshop MMBnet, 2007.
16. R. J. Lewis, "An introduction to classification and regression tree (cart) analysis, " in Annual Meeting of the Society for Academic Emergency Medicine in San Francisco, California, 2000, pp. 1-14.