DIFFUSE - Related Papers and Interim Reports

By members of CAIA

Journal and Conference Papers

• S. Zander, T. T. T. Nguyen, G. Armitage, "Sub-flow Packet Sampling for Scalable ML Classification of Interactive Traffic",  (accepted at) 37th Annual IEEE Conference on Local Computer Networks (LCN), Clearwater, Florida, USA, October 2012.
• T. T. T. Nguyen, G. Armitage, P. Branch, S. Zander, “Timely and Continuous Machine-Learning-Based Classification for Interactive IP Traffic”, IEEE/ACM Transactions on Networking, (in press) http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6164288.
• S. Zander, G. Armitage, "Practical Machine Learning Based Multimedia Traffic Classification for Distributed QoS Management", 36th Annual IEEE Conference on Local Computer Networks (LCN), Bonn, Germany, October 2011.
• T.T.T. Nguyen, G. Armitage, "A Survey of Techniques for Internet Traffic Classification using Machine Learning", IEEE Communications Surveys & Tutorials, vol. 10 no. 4 pp. 56-76, 2008.
• T.T.T. Nguyen, G. Armitage, "Clustering to Assist Supervised Machine Learning for Real-Time IP Traffic Classification", IEEE International Conference on Communications (ICC 2008), pp. 5857-5862, Beijing, China, 19-23 May 2008. 
• T.T.T. Nguyen, G. Armitage, "Synthetic Sub-flow Pairs for Timely and Stable IP Traffic Identification", Proc. Australian Telecommunication Networks and Application Conference 2006, Melbourne, Australia 4-6 December 2006.
• T.T.T.Nguyen, G.Armitage, "Training on multiple sub-flows to optimise the use of Machine Learning classifiers in real-world IP networks", Proc. IEEE 31st Conference on Local Computer Networks, Tampa, Florida, USA, November 2006.
• N. Williams, S. Zander, G. Armitage, "A Preliminary Performance Comparison of Five Machine Learning Algorithms for Practical IP Traffic Flow Classification", SIGCOMM Computer Communication Review, October 2006.
• S. Zander, N. Williams, G. Armitage, "Internet Archeology: Estimating Individual Application Trends in Incomplete Historic Traffic Traces", (poster) Passive and Active Measurement Workshop (PAM 2006),  Adelaide, Australia, March 30 - 31, 2006. [full paper]
• S. Zander, T.T.T. Nguyen, G. Armitage, "Automated Traffic Classification and Application Identification using Machine Learning", Proceedings of IEEE 30th Conference on Local Computer Networks (LCN 2005), Sydney, Australia, 15-17 November 2005.
• S. Zander, T.T.T. Nguyen, G. Armitage, "Self-learning IP Traffic Classification based on Statistical Flow Characteristics", (short paper) Passive and Active Measurement Workshop (PAM 2005), Boston, USA, March / April 2005.

Tech Reports and Talks

• N. Williams, S. Zander, "Real Time Traffic Classification and Prioritisation on a Home Router using DIFFUSE", (pdf) CAIA Technical Report 120412A, April 2012.
• S. Zander, G. Armitage, "Design of DIFFUSE v0.4 -- DIstributed Firewall and Flow-shaper Using Statistical Evidence", (pdf) CAIA Technical Report 110704A, July 2011.
• S. Zander, G. Armitage, "Design of DIFFUSE v0.1 -- DIstributed Firewall and Flow-shaper Using Statistical Evidence", (pdf) CAIA Technical Report 101223A, December 2010.
• S. Zander, N. Williams, G. Armitage, "Internet Archeology: Estimating Individual Application Trends in Incomplete Historic Traffic Traces", (pdf) CAIA Technical Report 060313A, March 2006.
• N. Williams, S. Zander, G. Armitage, "Evaluating Machine Learning Algorithms for Automated Network Application Identification", (pdf) CAIA Technical Report 060410B, April 2006.
• N. Williams, S. Zander, G. Armitage, "Evaluating Machine Learning Methods for Online Game Traffic Identification", (pdf) CAIA Technical Report 060410C, April 2006.
• S. Zander, "Misclassification of Game Traffic based on Port Numbers: A Case Study using Enemy Territory", (pdf) CAIA Technical Report 060410D, April 2006.
• N. Williams, "netAI - Network Traffic based Application Identifier", (pdf) CAIA Technical Report 060410E, April 2006.

By the wider community

Machine Learning for Traffic Classification

• X. Tian, Q. Sun, X. Huang, Y. Ma, "A Dynamic Online Traffic Classification Methodology Based on Data Stream Mining", World Congress on Computer Science and Information Engineering, 2009.
• M. Pietrzyk, G. Urvoy-Keller, J.-L. Costeux, "Revealing the Unknown ADSL Traffic Using Statistical Methods", COST TMA Workshop, 2009.
• X. Tian, Q. Sun, X. Huang, Y. Ma, "Dynamic Online Traffic Classification Using Data Stream Mining", International Conference on Multimedia and Information Technology, Washington, DC, USA, December 2008.
• Z. Guangxing, X. Gaogang, Y. Jianhua, "Accurate Online Traffic Classification with Multi-phases Identification Methodology", IEEE Consumer Communications & Networking Conference (CCNC), January 2008.
• D. Bonfiglio, M. Mellia, M. Meo, D. Rossi, P. Tofanelli, "Revealing Skype traffic: when randomness plays with you", Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications (SIGCOMM), New York, NY, USA, August 2007.
• J. Erman, A. Mahanti, M. Arlitt, "Byte me: a case for byte accuracy in traffic classification", 3rd Annual ACM Workshop on Mining Network Data (MineNet), New York, NY, USA, June 2007.
• J. Erman, A. Mahanti, M. Arlitt, C. Williamson, "Identifying and discriminating between web and peer-to-peer traffic in the network core", 16th International Conference on World Wide Web, Banff, Alberta, Canada, May 2007.
• J. Erman, A. Mahanti, M. Arlitt, I. Cohen, C. Williamson, "Semi-supervised network traffic classification", ACM International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS) Performance Evaluation Review, vol. 35, no. 1, pp. 369–370, 2007.
• T. Auld, A. W. Moore, S. F. Gull, "Bayesian neural networks for Internet traffic classification", IEEE Transactions Neural Networks, no. 1, pp. 223–239, January 2007.
• M. Crotti, M. Dusi, F. Gringoli, L. Salgarelli, "Traffic classification through simple statistical fingerprinting", SIGCOMM Computer Communication Review, vol. 37, no. 1, pp. 5–16, 2007.
• L. Bernaille, R. Teixeira, K. Salamatian, "Early Application Identification", 2nd ADETTI/ISCTE CoNEXT Conference, Lisboa, Portugal, December 2006.
• J. Park, H.-R. Tyan, K. C.-C.J., "GA-Based Internet Traffic Classification Technique for QoS Provisioning", International Conference on Intelligent Information Hiding and Multimedia Signal Processing, Pasadena, California, December 2006.
• J. Erman, A. Mahanti, and M. Arlitt, "Internet traffic identification using machine learning techniques", 49th IEEE Global Telecommunications Conference (GLOBECOM), San Francisco, USA, December 2006.
• J. Erman, M. Arlitt, A. Mahanti, "Traffic classification using clustering algorithms", SIGCOMM Workshop on Mining Network Data (MineNet), New York, NY, USA, 2006.
• C. Livadas, R. Walsh, D. Lapsley, "Using Machine Learning Techniques to Identify Botnet Traffic", IEEE Conference on Local Computer Networks (LCN), November 2006.
• W. Rui, L. Yang, Y. Yuexiang, Z. Xiaoyong, "Solving the App-Level Classification Problem of P2P Traffic Via Optimized Support Vector Machines", International Conference on Intelligent Systems Design and Applications (ISDA), October 2006.
• J. Ma, K. Levchenko, C. Kreibich, S. Savage, G. Voelker, "Unexpected means of protocol inference", 6th ACM SIGCOMM Conference on Internet Measurement, Rio de Janeriro, Brazil, October 2006.
• J. Park, H.-R. Tyan, K. C.-C.J., "Internet traffic classification for scalable QoS provision", IEEE International Conference on Multimedia and Expo, Toronto, Ontario, Canada, July 2006.
• L. Bernaille, R. Teuxeira, I. Akodkenou, A. Soule, K. Salamatian, "Traffic Classification on the Fly", ACM SIGCOMM Computer Communication Review, vol. 36, no. 2, April 2006.
• M. Barreno, B. Nelson, R. Sears, A. D. Joseph, J. D. Tygar, "Can machine learning be secure?", ACM Symposium on Information, Computer and Communications Security (ASIACCS),  Taipei, Taiwan, March 2006.
• P. Haffner, S. Sen, O. Spatscheck, D. Wang, "ACAS: automated construction of application signatures", ACM SIGCOMM workshop on Mining Network Data (MineNet), Philadelphia, Pennsylvania, USA, August 2005.
• T. Karagiannis, K. Papagiannaki, and M. Faloutsos, "BLINC: Multilevel Traffic Classification in the Dark", ACM Sigcomm 2005, Philadelphia, PA, USA, August 2005.
• Denis Zuev, Andrew Moore, "Internet traffic classification using bayesian analysis techniques", ACM SIGMETRICS 2005, Banff, Canada, June, 2005.
• Denis Zuev, Andrew Moore, "Traffic Classification using a Statistical Approach", Passive & Active Measurement Workshop, Boston, U.S.A, April 2005.
• A. Moore, and K. Papagiannaki, "Toward the Accurate Identification of Network Applications", Passive & Active Measurement Workshop, Boston, U.S.A., April, 2005.
• M. Roughan, S. Sen, O. Spatscheck, N. Duffield, "Class-of-Service Mapping for QoS: A statistical signature-based approach to IP traffic classification", ACM SIGCOMM Internet Measurement Workshop 2004, Taormina, Sicily, Italy, 2004.
• A. McGregor, M. Hall, P. Lorier, J. Brunskill, "Flow Clustering Using Machine Learning Techniques", Passive & Active Measurement Workshop 2004 (PAM 2004), France, April 19-20, 2004.
• James P. Early, Carla E. Brodley, and Catherine Rosenburg, "Behavioral Authentication of Server Flows", Proceedings of the 19th Annual Computer Security Applications Conference, Las Vegas, NV, USA, December 2003.
• A. Soule, K. Salamatian, N. Taft, R. Emilion, K. Papagiannaki, "Flow Classification by Histograms or How to Go on Safari in the Internet", In ACM Sigmetrics, New York, U.S.A., June, 2004.
• T. Dunnigan, G. Ostrouchov, "Flow Characterization for Intrusion Detection", Oak Ridge National Laboratory, Technical Report, November 2000.
  

Machine Learning Techniques and Algorithms

• Ian H. Witten, Eibe Frank,  "Data Mining: Practical Machine Learning Tools and Techniques (Second Edition)", Morgan Kaufmann, June 2005.
• Tom M. Mitchell, “Machine Learning”, McGraw-Hill Education (ISE Editions), December 1997.
• Tom M. Mitchell, “Does Machine Learning Really Work?”, AI Magazine 18(3), pp. 11-20, 1997.
• T. G. Dietterich, “Machine-Learning Research – Four Current Directions”, American Association for Artificial Intelligence, 1997.