References

Altwaijry, H., 2013. Bayesian Based Intrusion Detection System. In: IAENG Transactions on Engineering Technologies, Kim, H.K., S.I. Ao and B.B. Rieger (Eds.). Springer, New York, USA., ISBN: 9789400747869, pp: 29-44.

Bankovic, Z., D. Stepanovic, S. Bojanic and O. Nieto-Taladriz, 2007. Improving network security using genetic algorithm approach. Comput. Electr. Eng., 33: 438-451.
CrossRef  |  

Buyya, R., J. Giddy and D. Abramson, 2013. An evaluation of economy-based resource trading and scheduling on computational power grids for parameter sweep applications. Proceedings of the 2nd International Annual Workshop on Active Middleware Services, October 4, 2013, Edinburgh -.

Chandola, V., A. Banerjee and V. Kumar, 2012. Anomaly detection for discrete sequences: A survey. IEEE Trans. Knowledge Data Eng., 24: 823-839.
CrossRef  |  

Che, Z. and X. Ji, 2012. An efficient intrusion detection approach based on hidden markov model and rough set. Proceedings of the International Conference on Machine Vision and Human-Machine Interface, April 24-25, 2010, Kaifeng, China, pp: 476-479.

Guo, Y., B. Wang, X. Zhao, X. Xie, L. Lin and Q. Zhou, 2010. Feature selection based on rough set and modified genetic algorithm for intrusion detection. Proceedings of the 5th International Conference on Computer Science and Education (ICCSE), August 24-27, 2010, Hefei, Anhui, P.R. China, Pp: 1441-1446.

Li, Y., J. Xia, S. Zhang, J. Yan, X. Ai and K. Dai, 2012. An efficient intrusion detection system based on support vector machines and gradually feature removal method. Expert Syst. Appl., 39: 424-430.
CrossRef  |  Direct Link  |  

Mar, J., Y.C. Yeh and I.F. Hsiao, 2014. An ANFIS-IDS against deauthentication DOS attacks for a WLAN. Proceedings of the International Symposium on Information Theory and its Applications, October 17-20, 2010, Taichung, pp: 548-553.

Memon, V.I. and G.S. Chandel, 2014. A design and implementation of new hybrid system for anomaly intrusion detection system to improve efficiency. Int. J. Eng. Res. Applic., 4: 1-7.
Direct Link  |  

Muda, Z., W. Yassin, M.N. Sulaiman and N.I. Udzir, 2011. Intrusion detection based on K-means clustering and Naive bayes classification. Proceedings of the 7th International Conference on Information Technology in Asia, July 12-13, 2011, Kuching, Sarawak, pp: 1-6.

Mukhopadhyay, I., M. Chakraborty, S. Chakrabarti and T. Chatterjee, 2011. Back propagation neural network approach to intrusion detection system. Proceedings of the 2011 International Conference on Recent Trends in Information Systems, December 21-23, 2011, Kolkata, pp: 303-308.

Rupali, D. and V. Bhupendra, 2010. Feature reduction for intrusion detection using linear discriminant analysis. Int. J. Comput. Sci. Eng., 2: 1072-1078.

Salah, S., G. Macia-Fernandez and J.E. Diaz-Verdejo, 2013. A model-based survey of alert correlation techniques. Comput. Networks, 57: 1289-1317.
CrossRef  |  Direct Link  |  

Sangkatsanee, P., N. Wattanapongsakorn and C. Charnsripinyo, 2011. A practical network-based intrusion detection and prevention system. Comput. Commun., 34: 2227-2235.

Song, J., H. Takakura, Y. Okabe and K. Nakao, 2013. Toward a more practical unsupervised anomaly detection system. Inf. Sci., 231: 4-14.
CrossRef  |  Direct Link  |