References

Abdel-Fattah, F., Z.M. Dahalin and S. Jusoh, 2010. Dynamic intrusion detection method for mobile ad hoc network using CPDOD algorithm. IJCA Special Issue MANETs, 1: 22-29.

Bu, S., F.R. Yu, X.P. Liu, P. Mason and H. Tang, 2011. Distributed combined authentication and intrusion detection with data fusion in high-security mobile ad hoc networks. IEEE Trans. Vehicular Technol., 60: 1025-1036.
CrossRef  |  

Burges, C.J.C., 1998. A tutorial on support vector machines for pattern recognition. Data Mining Knowl. Discov., 2: 121-167.
CrossRef  |  Direct Link  |  

Chen, R.C., K.F. Cheng and C.F. Hsieh, 2009. Using rough set and support vector machine for network intrusion detection. Proceedings of the 1st Asian Conference on Intelligent Information and Database Systems, April 1-3, 2009, Dong Hoi, pp: 465-470.

Joseph, J.F.C., B.S. Lee, A. Das and B.C. Seet, 2011. Cross-layer detection of sinking behavior in wireless ad hoc networks using SVM and FDA. IEEE Trans. Dependable Secure Comput., 8: 233-245.
CrossRef  |  

Liu, Y., Y. Li and H. Man, 2005. Short paper: A distributed cross-layer intrusion detection system for ad hoc networks. Proceedings of the 1st International Conference on Security and Privacy for Emerging Areas in Communications Networks, September 5-9, 2005, Baltimore, Maryland, pp: 418-420.

Mishra, A., K. Nadkarni and A. Patcha, 2004. Intrusion detection in wireless ad hoc networks. IEEE Wireless Communicat., 11: 48-60.
CrossRef  |  

Mohammed, N., H. Otrok, L. Wang, M. Debbabi and P. Bhattacharya, 2011. Mechanism design-based secure leader election model for intrusion detection in MANET. IEEE Trans. Dependable Secure Comput., 8: 89-103.
CrossRef  |  

Nakayama, H., S. Kurosawa, A. Jamalipour, Y. Nemoto and N. Kato, 2009. A dynamic anomaly detection scheme for AODV-based mobile ad hoc networks. IEEE Trans. Vehicular Technol., 58: 2471-2481.
CrossRef  |  

Ning, P. and K. Sun, 2003. How to misuse AODV: A case study of insider attacks against mobile ad-hoc routing protocols. Proceedings of the Systems, Man and Cybernetics Society on Information Assurance Workshop, June 18-20, 2003, IEEE Computer Society, USA., pp: 60-67.

Ohrn, A. and J. Komorowski, 1997. A rough set toolkit for analysis of data. Proceedings of the 3rd Joint Conference on Information Sciences, Volume 3, March 11-14, 1997, Burlingame, CA., pp: 403-407.

Parthalain, N.S.M., 2009. Rough set extensions for feature selection. Ph.D. Thesis, Department of Computer Science, Aberystwyth University, Aberystwyth, United Kingdom.

Pastrana, S., A. Mitrokotsa, A. Orfila and P. Peris-Lopez, 2012. Evaluation of classification algorithms for intrusion detection in manets. Knowl. Based Syst., 36: 217-225.
CrossRef  |  

Pawlak, Z., 1998. Some Issues on Rough Sets. In: Transactions on Rough Sets I, Peters, J.F. and A. Skowron (Eds.). Springer, New York, pp: 1-58.

Perkins, C., E. Belding-Royer and S. Das, 2003. Ad hoc On-Demand Distance Vector (AODV) routing. Network Working Group, Request for Comments: 3561 July 2003. http://www.ietf.org/rfc/rfc3561.txt.

Sen, S. and J.A. Clark, 2011. Evolutionary computation techniques for intrusion detection in mobile ad hoc networks. Comput. Networks, 55: 3441-3457.
CrossRef  |  

Shrivastava, K.S. and P. Jain, 2011. Effective anomaly based intrusion detection using rough set theory and support vector machine. Int. J. Comput. Appl., 8: 35-41.
CrossRef  |  

Tsai, C.F., Y.F. Hsu, C.Y. Lin and W.Y. Lin, 2009. Intrusion detection by machine learning: A review. Exp. Syst. Applic., 36: 11994-12000.
CrossRef  |  Direct Link  |