S. Alcock and R. Nelson, Libprotoident: Traffic Classification Using Lightweight Packet Inspection, 2012.

N. , A. Khater, and R. Overill, Forensic network traffic analysis, Proceedings of the Second International Conference on Digital Security and Forensics, 2015.

T. Auld, A. Moore, and S. Gull, Bayesian neural networks for Internet traffic classification, IEEE Transactions on Neural Networks, vol.18, issue.1, pp.223-239, 2007.

L. Breiman, Random forests, Machine Learning, vol.45, pp.5-32, 2001.

E. Bursztein, Probabilistic identification of hard to classify protocols, Proceedings of the Second IFIP WG 11.2 International Conference on Information Security Theory and Practices: Smart Devices, Convergence and Next Generation Networks, pp.49-63, 2008.

S. Dai, A. Tongaonkar, X. Wang, A. Nucci, and D. Song, NetworkProfiler: Towards automatic fingerprinting of Android apps, Proceedings of the IEEE International Conference on Computer Communications, pp.809-817, 2013.

M. Deza and E. Deza, Encyclopedia of Distances, 2009.

J. Erman, A. Mahanti, M. Arlitt, I. Cohen, and C. Williamson, Offline/real-time traffic classification using semi-supervised learning, Performance Evaluation, vol.64, pp.1194-1213, 2007.

A. Finamore, M. Mellia, and M. Meo, Mining unclassified traffic using automatic clustering techniques, Proceedings of the Third International Conference on Traffic Monitoring and Analysis, pp.150-163, 2011.

V. Foroushani and A. Zincir-heywood, Investigating application behavior in network traffic traces, Proceedings of the IEEE Symposium on Computational Intelligence for Security and Defense Applications, pp.72-79, 2013.

N. Friedman, D. Geiger, and M. Goldszmidt, Bayesian network classifiers, Machine Learning, vol.29, pp.131-163, 1997.

G. , G. Sena, and P. Belzarena, Early traffic classification using support vector machines, Proceedings of the Fifth International Latin American Networking Conference, pp.60-66, 2009.

I. Guyon and A. Elisseeff, An introduction to variable and feature selection, Journal of Machine Learning Research, vol.3, pp.1157-1182, 2003.

J. Han, M. Kamber, and J. Pei, Data Mining: Concepts and Techniques, 2012.

T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning-Data Mining, Inference and Prediction, 2009.

E. Hjelmvik, The SPID Algorithm-Statistical Protocol Identification, 2008.

J. Khalife, A. Hajjar, and J. Diaz-verdejo, A multilevel taxonomy and requirements for an optimal traffic-classification model, International Journal of Network Management, vol.24, issue.2, pp.101-120, 2014.

J. Kittler, Combining classifiers: A theoretical framework, Pattern Analysis and Applications, vol.1, issue.1, pp.18-27, 1998.

C. Kohnen, C. Uberall, F. Adamsky, V. Rakocevic, M. Rajarajan et al., Enhancements to statistical protocol identification (SPID) for self-organized QoS in LANs, Proceedings of the Nineteenth International Conference on Computer Communications and Networks, 2010.

J. Li, S. Zhang, Y. Xuan, and Y. Sun, Identifying Skype traffic by random forests, Proceedings of the International Conference on Wireless Communications, Networking and Mobile Computing, pp.2841-2844, 2007.

Y. Luo, K. Xiang, and S. Li, Acceleration of decision tree searching for IP traffic classification, Proceedings of the Fourth ACM/IEEE Symposium on Architectures for Networking and Communications Systems, pp.40-49, 2008.

P. Matousek, J. Pluskal, O. Rysavy, V. Vesely, M. Kmet et al., Advanced techniques for reconstruction of incomplete network data, Proceedings of the Seventh International Conference on Digital Forensics and Cyber Crime, pp.69-84, 2015.

S. Miskovic, G. Lee, Y. Liao, and M. Baldi, AppPrint: Automatic fingerprinting of mobile applications in network traffic, Proceedings of the Sixteenth International Conference on Passive and Active Measurement, pp.57-69, 2015.

A. Moore and K. Papagiannaki, Toward the accurate identification of network applications, Proceedings of the Sixth International Workshop on Passive and Active Network Measurement, pp.41-54, 2005.

A. Moore, D. Zuev, and M. Crogan, Discriminators for Use in FlowBased Classification, 2013.

N. Namdev, S. Agrawal, and S. Silkari, Recent advancements in machine learning based Internet traffic classification, Procedia Computer Science, vol.60, pp.784-791, 2015.

T. Nguyen and G. Armitage, A survey of techniques for Internet traffic classification using machine learning, IEEE Communications Surveys and Tutorials, vol.10, issue.4, pp.56-76, 2008.

C. Shen and L. Huang, On the detection accuracy of the l7-filter and OpenDPI, Proceedings of the Third International Conference on Networking and Distributed Computing, pp.119-123, 2012.

P. Velan, M. Cermak, P. Celeda, and M. Drasar, A survey of methods for encrypted traffic classification and analysis, International Journal of Network Management, vol.25, issue.5, pp.355-374, 2015.

Y. Wang and S. Yu, Machine learned real-time traffic classifiers, Proceedings of the Second International Symposium on Intelligent Information Technology Applications, vol.3, pp.449-454, 2008.

I. Zezula, On multivariate Gaussian copulas, Journal of Statistical Planning and Inference, vol.139, issue.11, pp.3942-3946, 2009.

L. Zhen and L. Qiong, A new feature selection method for Internet traffic classification using ML, Physics Procedia, vol.33, pp.1338-1345, 2012.