A network intrusion detection system based on a Hidden Naïve Bayes multiclass classifier

Author:

Koc Levent,Mazzuchi Thomas A.,Sarkani Shahram

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference65 articles.

1. Ambwani, T. (2003). Multi class support vector machine implementation to intrusion detection. In Paper presented at the international joint conference on neural networks, 20–24 July.

2. Baig, Z. A., Shaheen, A. S., & AbdelAal, R. (2011). An AODE-based intrusion detection system for computer networks. In Paper presented at the world congress on internet security (WorldCIS) (Feb., pp. 21–23).

3. Baker, S., Filipiak, N., & Timlin, K. (2011). In the dark: crucial industries confront cyberattacks McAfee annual critical infrastructure protection report (2nd ed.). Santa Clara, CA: The Center for Strategic and International Studies (CSIS).

4. Barbara, D., Wu, N., & Jajodia, S. (2001). Detecting novel network intrusions using Bayes estimators. In Paper presented at the first SIAM conference on data mining, Chicago, IL.

5. Benferhat, S., Boudjelida, A., & Drias, H. (2008). On the use of TAN in intrusion detection systems. In Proceedings of the second international conference on information processing (pp. 1–13).

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