Information Technology Reference
In-Depth Information
Faysel, M. A., & Haque, S. S. (2010). Towards cyber defense: research in intrusion detection and
intrusion prevention systems. IJCSNS International Journal of Computer Science and Network
Security, 10(7), 316 - 325.
Feizollah, A., Anuar, N. B., Salleh, R., Amalina, F., Ma ' arof, R. U. R., & Shamshirband, S.
(2014). A study of machine learning classifiers for anomaly-based mobile Botnet detection.
Malaysian Journal of Computer Science, 26(4), 251
265.
Gong, R. H., Zulkernine, M., & Abolmaesumi, P. (2005, May). A software implementation of a
genetic algorithm based approach to network intrusion detection. In Sixth international
conference on software engineering, artificial intelligence, networking and parallel/distributed
computing, 2005 and first ACIS international workshop on self-assembling wireless networks
(SNPD/SAWN 2005) (pp. 246
-
253). IEEE.
Guisan, A., & Thuiller, W. (2005). Predicting species distribution: Offering more than simple
habitat models. Ecology Letters, 8(9), 993
-
1009.
Gupta, B. B., Joshi, R. C., & Misra, M. (2012). ANN based scheme to predict number of Zombies
in a DDoS attack. IJ Network Security, 14(2), 61
-
70.
Han, L. (2012). Research of K-MEANS algorithm based on information Entropy in Anomaly
Detection. In Multimedia Information Networking and Security (MINES), November 2012
Fourth International Conference on (pp. 71-74). IEEE.
Haykin, S. (2005). Neural networks a comprehensive foundation. New Delhi: Pearson Education.
Heady R., Luger G., Maccabe A., & Servilla M. (1990, August). The architecture of a network
level intrusion detection system. Technical report, Computer Science Department, University
of New Mexico.
Hwang, R. C., Chen, Y. J., & Huang, H. C. (2010). Artificial intelligent analyzer for mechanical
properties of rolled steel bar by using neural networks. Expert Systems with Applications, 37
(4), 3136
-
3139.
Ibrahim, L. M., Basheer, D. T., & Mahmod, M. S. (2013). A comparison study for intrusion
database (Kdd99, Nsl-Kdd) based on self organization map (SOM) artificial neural network.
Journal of Engineering Science and Technology, 8(1), 107
-
119.
Khashei, M., Rezvan, M. T., Hamadani, A. Z., & Bijari, M. (2013). A bi-level neural-based fuzzy
classi cation approach for credit scoring problems. Complexity, 18(6), 46
-
57.
Kuanf, F., Xu, W., Zhang, S., Wang,Y., & Liu, K. (2012). A novel Approach of KPCA and SVM
for Intrusion Detection, Journal of Computational Information Systems, pp 3237
-
3244.
Kuo, R. J., Wang, Y. C., & Tien, F. C. (2010). Integration of arti cial neural network and MADA
methods for green supplier selection. Journal of Cleaner Production, 18(12), 1161 - 1170.
Laskov, P., D ü ssel, P., Sch ä fer, C., & Rieck, K. (2005). Learning intrusion detection: Supervised
or unsupervised? In Image analysis and processing ICIAP 2005 (pp. 50 - 57). Berlin
Heidelberg: Springer.
Lee, W., Stolfo, S. J., & Mok, K. W. (1999). A data mining framework for building intrusion
detection models. In Proceedings of the 1999 IEEE symposium on security and privacy
(pp. 120
-
132). IEEE.
Liao, Y., & Vemuri, V. R. (2002). Use of K-nearest neighbor classifier for intrusion detection.
Computers and Security, 21(5), 439
-
448.
Liu, J. (2013). An adaptive intrusion detection model based on ART2 neural network. Journal of
Computational Information Systems, 9(19), 7775
-
7782.
Louvieris, P., Clewley, N., & Liu, X. (2013). Effects-based feature identification for network
intrusion detection. Neurocomputing, 121, 265
-
273.
McCarthy, J., Minsky, M. L., Rochester, N., & Shannon, C. E. (1955). A proposal for the dartmouth
summer research project on arti cial intelligence, August 31, 1955. AI Magazine, 27(4), 12.
McCarthy, J. (2007). What is arti cial intelligence. url: http://www-formal.stanford.edu/jmc/
whatisai.html . (accessed on 22 November 2013)
Mukhopadhyay, I., Chakraborty, M., Chakrabarti, S., & Chatterjee, T. (2011). Back propagation
neural network approach to Intrusion Detection System. In Recent Trends in Information
Systems (ReTIS), December 2011 International Conference on (pp. 303 - 308). IEEE.
-
Search WWH ::




Custom Search