W. Lee and D. Xiang, Information-theoretic measures for anomaly detection, Proceedings of 2001 IEEE Symposium on Security and Privacy, pp.130-143, 2001.

. Syngress, Snort 2.1 Intrusion Detection, 2004.

S. Kumar and E. H. Spafford, A Software architecture to support misuse intrusion detection, Proceedings of the 18th National Information Security Conference, pp.194-204, 1995.

D. E. Denning, An intrusion-detection model, IEEE Transactions on Software Engineering, vol.13, issue.2, pp.222-232, 1987.

S. Forrest, S. A. Hofmeyr, A. Somayaji, and T. A. Longstaff, A sense of self for Unix processes, Proceedings 1996 IEEE Symposium on Security and Privacy, pp.120-128, 1996.
DOI : 10.1109/SECPRI.1996.502675

C. Warrender, S. Forrest, and B. Pearlmutter, Detecting intrusions using system calls: alternative data models, Proceedings of the 1999 IEEE Symposium on Security and Privacy (Cat. No.99CB36344), pp.133-145, 1999.
DOI : 10.1109/SECPRI.1999.766910

W. Wang and S. Gombault, Distance measures for anomaly intrusion detection, Proceedings of 2007 internatinal conference on security and management, SAM'07, pp.15-21, 2007.
URL : https://hal.archives-ouvertes.fr/hal-01898076

W. Wang, X. Guan, X. Zhang, and L. Yang, Profiling program behavior for anomaly intrusion detection based on the transition and frequency property of computer audit data, Computers & Security, vol.25, issue.7, pp.539-550, 2006.
DOI : 10.1016/j.cose.2006.05.005

W. Lee, S. Stolfo, and K. Mok, A Data Mining Framework for Building Intrusion Detection Models, Proceedings of the 1999 IEEE Symposium on Security and Privacy, pp.120-132, 1999.

W. Lee and S. Stolfo, A framework for constructing features and models for intrusion detection systems, ACM Transactions on Information and System Security, vol.3, issue.4, pp.227-261, 2000.
DOI : 10.1145/382912.382914

, 12] KDD Cup 1999 data (Computer network intrusion detection), 1999.

E. Eskin, A. Arnold, M. Prerau, L. Portnoy, and S. Stolfo, A Geometric Framework for Unsupervised Anomaly Detection, 2002.
DOI : 10.1007/978-1-4615-0953-0_4

S. Jin, D. Yeung, and X. Wang, Network intrusion detection in covariance feature space, Pattern Recognition, vol.40, issue.8, pp.2185-2197, 2007.
DOI : 10.1016/j.patcog.2006.12.010

V. Katos, Network intrusion detection: Evaluating cluster, discriminant, and logit analysis, Information Sciences, vol.177, issue.15, pp.3060-3073, 2007.
DOI : 10.1016/j.ins.2007.02.034

M. Shyu, S. Chen, K. Sarinnapakorn, and L. Chang, Principal Componentbased Anomaly Detection Scheme, Foundations and Novel Approaches in Data Mining, pp.311-329, 2006.
DOI : 10.1007/11539827_18

S. Mukkamala, A. H. Sunga, and A. Abrahamb, Intrusion detection using an ensemble of intelligent paradigmsProcessing of Massive Audit Data Streams for Real-Time Anomaly Intrusion Detection, Journal of Network and Computer Applications, pp.167-182, 2005.

W. Wang, S. Gombault, and A. Bsila, Building multiple behavioral models for network intrusion identification, 2nd IEEE Workshop on Monitoring, Attack Detection and Mitigation, pp.31-36, 2007.

W. Wang and R. Battiti, Identifying intrusions in computer networks with principal component analysis, First International Conference on Availability, Reliability and Security (ARES'06), pp.270-277, 2006.
DOI : 10.1109/ARES.2006.73
URL : http://rtm.science.unitn.it/~battiti/archive/ares2006.pdf

Y. Bouzida and F. Cuppens, Neural networks vs. decision trees for intrusion detection, First IEEE workshop on Monitoring, Attack Detection and Mitigation, 2006.

Y. Bouzida, F. Cuppens, N. Cuppens-boulahia, and S. Gombault, Efficient intrusion detection using principal component analysis, 3ème Conférence sur la Sécurité et Architectures Réseaux, 2004.

L. Yu and H. Liu, Feature Selection for High-Dimensional Data: A Fast Correlation-Based Filter Solution, pp.856-863, 2003.

A. H. Sung and S. Mukkamala, Identifying important features for intrusion detection using support vector machines and neural networks, 2003 Symposium on Applications and the Internet, 2003. Proceedings., 2003.
DOI : 10.1109/SAINT.2003.1183050

S. Das, Filters, wrappers and a boosting-based hybrid for feature selection, pp.74-81, 2001.

D. Heckerman, . Tutorial-on-learning-with-bayesian, M. Networks, and . Research, , 1995.

R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification, 2004.

J. R. Quinlan, C4.5: Programs for Machine Learning, 1993.