K. Egevang and P. Francis, The IP Network Address Translator (NAT) Request For Comments, Informational), p.1631, 1994.

B. Claise, S. Bryant, S. Leinen, T. Dietz, and B. H. Trammell, Specification of the IP Flow Information Export (IPFIX) Protocol for the Exchange of IP Traffic Flow Information, 2007.
DOI : 10.17487/rfc5101

B. E. Boser, I. M. Guyon, and V. N. Vapnik, A training algorithm for optimal margin classifiers, Proceedings of the fifth annual workshop on Computational learning theory , COLT '92, pp.144-152, 1992.
DOI : 10.1145/130385.130401
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.103.1189

K. Dyer, S. Coull, T. Ristenpart, and T. Shrimpton, Peek-a-Boo, I Still See You: Why Efficient Traffic Analysis Countermeasures Fail, 2012 IEEE Symposium on Security and Privacy, pp.332-346, 2012.
DOI : 10.1109/SP.2012.28
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.300.3506

P. Li, Y. Wang, and X. Tao, A Semi-Supervised Network Traffic Classification Method Based on Incremental Learning, Proceedings of the 2012 International Conference on Information Technology and Software Engineering, pp.955-964, 2013.
DOI : 10.1007/978-3-642-34522-7_100

T. Tabatabaei, F. Karray, and M. Kamel, Early internet traffic recognition based on machine learning methods, 2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), pp.1-5, 2012.
DOI : 10.1109/CCECE.2012.6335034

J. Francois, C. Wagner, R. State, and T. Engel, SAFEM: Scalable analysis of flows with entropic measures and SVM, 2012 IEEE Network Operations and Management Symposium, pp.510-513, 2012.
DOI : 10.1109/NOMS.2012.6211943
URL : https://hal.archives-ouvertes.fr/hal-00734967

C. H. Hsu, C. Y. Huang, and K. T. Chen, Fast-Flux Bot Detection in Real Time, Lecture Notes in Computer Science, vol.6307, pp.464-483, 2010.
DOI : 10.1007/978-3-642-15512-3_24
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.667.9226

P. Barthakur, M. Dahal, and M. Ghose, A Framework for P2P Botnet Detection Using SVM, 2012 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, pp.195-200, 2012.
DOI : 10.1109/CyberC.2012.40

J. R. Quinlan, C4.5: programs for machine learning, 1993.

J. Rosenberg, R. Manhy, P. Matthews, and D. Wing, Session Traversal Utilities for NAT (STUN) Request For Comments 5389, 2008.

Y. Wei, D. Yamada, S. Yoshida, and S. Goto, A New Method for Symmetric NAT Traversal in UDP and TCP, Network, vol.4, issue.8, 2008.

S. M. Bellovin, A technique for counting natted hosts, Proceedings of the second ACM SIGCOMM Workshop on Internet measurment , IMW '02, pp.267-272, 2002.
DOI : 10.1145/637201.637243

J. Bi, M. Zhang, and L. Zhao, Security Enhancement by Detecting Network Address Translation Based on Instant Messaging, Proceedings of the 2006 international conference on Emerging Directions in Embedded and Ubiquitous Computing . EUC'06, pp.962-971, 2006.
DOI : 10.1007/11807964_97

T. Kohno, A. Broido, and K. C. Claffy, Remote Physical Device Fingerprinting, IEEE Transactions on Dependable and Secure Computing, vol.2, issue.2, pp.93-108, 2005.
DOI : 10.1109/TDSC.2005.26
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.134.7415

S. Schulz, A. R. Sadeghi, M. Zhdanova, H. Mustafa, W. Xu et al., Tetherway, Proceedings of the fifth ACM conference on Security and Privacy in Wireless and Mobile Networks, WISEC '12, pp.149-160, 2012.
DOI : 10.1145/2185448.2185468

V. Krmí?ek, J. Vykopal, and R. Krej?í, Netflow based system for NAT detection, Proceedings of the 5th international student workshop on Emerging networking experiments and technologies, Co-Next Student Workshop '09, pp.23-24, 2009.
DOI : 10.1145/1658997.1659010

J. Steinberger, L. Schehlmann, S. Abt, and H. Baier, Anomaly Detection and Mitigation at Internet Scale: A Survey, Proceedings of the 7th International Conference on Autonomous Infrastructure, Management and Security, 2013.
DOI : 10.1007/978-3-642-38998-6_7
URL : https://hal.archives-ouvertes.fr/hal-01489970

L. Rui, Z. Hongliang, X. Yang, Y. Yixian, and W. Cong, Remote NAT Detect Algorithm Based on Support Vector Machine, ICIECS 2009. International Conference on Information Engineering and Computer Science, pp.1-4, 2009.

L. Rui, Z. Hongliang, X. Yang, L. Shoushan, Y. Yixian et al., Passive NATted Hosts Detect Algorithm Based on Directed Acyclic Graph Support Vector Machine, MINES '09. International Conference on Multimedia Information Networking and Security, pp.474-477, 2009.

J. C. Platt, N. Cristianini, and J. Shawe-taylor, Large Margin DAGs for Multiclass Classification, Advances in Neural Information Processing Systems, pp.547-553, 2000.

J. Xu, J. Fan, M. Ammar, and S. B. Moon, On the design and performance of prefix-preserving IP traffic trace anonymization, Proceedings of the First ACM SIGCOMM Workshop on Internet Measurement , IMW '01, pp.263-266, 2001.
DOI : 10.1145/505202.505234