The week's pick
Random Articles
Reseach Article
Attack Detection over Network based on C45 and RF Algorithms
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 57 - Number 9 |
| Year of Publication: 2012 |
| Authors: Sushil Kumar Chaturvedi, Vineet Richariya |
10.5120/9144-3368
|
Sushil Kumar Chaturvedi, Vineet Richariya . Attack Detection over Network based on C45 and RF Algorithms. International Journal of Computer Applications. 57, 9 ( November 2012), 29-34. DOI=10.5120/9144-3368
Abstract
In this paper, Intrusion detection is to detect attacks(Intrusions) against a computer system. In the highly networked modern world, conventional techniques of network security such as cryptography, user authentication and intrusion prevention techniques like firewalls are not sufficient to detect new attacks. In this paper, we perform experiments on the kddcup99 data set. We perform dimensionality reduction of the data set using PCA (principal Component Analysis) and clear distinction between normal and anomalous data is observed by using supervised data mining techniques. Primarily experiments with kddcup99 network data show that the supervised techniques such as Naïve Bayesian, C4. 5 can effectively detect anomalous attacks and achieve a low false positive rate. In this thesis optimization technique such as Random Forest has applied to improve the efficiency of detection rate and achieve a low false positive rate. This mechanism can effectively tolerate intrusion.
References
- M. Xue, C. Zhu, "Applied Research on Data Mining Algorithm in Network Intrusion Detection," jcai, pp. 275-277, 2009 International Joint Conference on Artificial Intelligence, 2009.
- D. E. Denning, "An intrusion detection model," IEEE Transaction on Software Engineering, 1987.
- T. Bhavani et al. , "Data Mining for Security Applications," Proceedings of the 2008 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing - Volume 02, IEEE Computer Society, 2008.
- T. Lappas and K. P. ,"Data Mining Techniques for (Network) Intrusion Detection System," January 2007.
- S. Sun, Y. Wang, "A Weighted Support Vector Clustering Algorithm and its Application in Network Intrusion Detection," etcs, vol. 1, pp. 352-355, 2009 First International Workshop on Education Technology and Computer Science, 2009.
- S. Wu, E. Yen. "Data mining-based intrusion detectors," Elsevier Computer Network, 2009.
- E. Bloedorn et al, "Data Mining for Network Intrusion Detection: How to Get Started," Technical paper, 2001.
- Dorothy E. Denning. "An Intrusion-Detection Model" 1986 IEEE Computer Society Symposium on Research in Security and Privacy , pp 118-31
- M. Govindarajan and RM. Chandrasekaran "Intrusion Detection using K-Nearest Neighbor" ICAC 2009 978-1-4244-4787-9/09 © 2009 IEEE
- Mohammadreza Ektefa , Sara Memar, Fatimah Sidi ,Lilly Suriani Affendey "Intrusion Detection Using Data Mining Techniques" 978-1-4244-5651-2/10 © 2010 IEEE.
- Michael D. Alder " An Introduction to Pattern Recognition: Statistical,Neural Net and Synthetic Methods of getting robots to see and hear", September19,1997http://ciips. ee. uwa. edu. au/mike/PatRec
- J. Zhang, and M. Zulkernine, 2006. A Hybrid Network Intrusion Detection Technique Using Random Forests. In Proceedings of the IEEE First International Conference on Availability, Reliability and Security(ARES'06).
- L. Breiman, "Random Forests", Machine Learning 45(1):5–32, 2001.
- White, Mark ECE591Q-Machine Learning – Lecture slides, Fall 2005
- T. M. Khoshgoftaar, M. Golawala and J. Van Hulse, "An Empirical Study of Learning from Imbalanced Data Using Random Forest. " Proceedings of the 19th. IEEE Conference on Tools with Artificial Intelligence. 2007, pp. 310-317.
- Nebu Varghese, Vinay Verghese, Prof. Gayathri. P and Dr. N. Jaisankar "A SURVEY OF DIMENSIONALITY REDUCTION AND CLASSIFICATION METHODS" International Journal of Computer Science & Engineering Survey (IJCSES) Vol. 3, No. 3, June 2012
- J. Han, and M. Kamber, "Data mining: concepts and techniques'"(2nd ed. ). Morgan Kaufmann Publishers, 2006.
- Naren Ramakrishnan "C4. 5" © 2009 by Taylor & Francis Group, LLC 2009.
- http://kdd. ics. uci. edu/databases/kddcup99/
- J. Han, and M. Kamber, "Data mining: concepts and techniques'" (2nd ed. ). Morgan Kaufmann Publishers, 2006.
- Prabhjeet Kaur , Amit Kumar Sharma, Sudesh Kumar Prajapat "MADAM ID FOR INTRUSION DETECTION USING DATA MINING" IJRIM Volume 2, Issue 2 (February 2012) (ISSN 2231-4334).
Index Terms
Keywords