Empirically derived analytic models of wide-area TCP connections
IEEE/ACM Transactions on Networking (TON)
Wide area traffic: the failure of Poisson modeling
IEEE/ACM Transactions on Networking (TON)
Internet traffic characterization
Internet traffic characterization
ICNP '02 Proceedings of the 10th IEEE International Conference on Network Protocols
An analysis of Internet chat systems
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Transport layer identification of P2P traffic
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
Internet traffic classification using bayesian analysis techniques
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Profiling internet backbone traffic: behavior models and applications
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
BLINC: multilevel traffic classification in the dark
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
Traffic classification through simple statistical fingerprinting
ACM SIGCOMM Computer Communication Review
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Early application identification
CoNEXT '06 Proceedings of the 2006 ACM CoNEXT conference
Toward the accurate identification of network applications
PAM'05 Proceedings of the 6th international conference on Passive and Active Network Measurement
A survey of techniques for internet traffic classification using machine learning
IEEE Communications Surveys & Tutorials
Bayesian Neural Networks for Internet Traffic Classification
IEEE Transactions on Neural Networks
Network prefix-level traffic profiling: Characterizing, modeling, and evaluation
Computer Networks: The International Journal of Computer and Telecommunications Networking
Session-based classification of internet applications in 3G wireless networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Timely and continuous machine-learning-based classification for interactive IP traffic
IEEE/ACM Transactions on Networking (TON)
Detection and classification of peer-to-peer traffic: A survey
ACM Computing Surveys (CSUR)
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The ability to accurately classify and identify the network traffic associated with different applications is a central issue for many network operation and research topics including Quality of Service enforcement, traffic engineering, security, monitoring and intrusion-detection. However, traditional classification approaches for traffic to higher-level application mapping, such as those based on port or payload analysis, are highly inaccurate for many emerging applications and hence useless in actual networks. This paper presents a recurrence plot-based traffic classification approach based on the analysis of non-stationary ''hidden'' transition patterns of IP traffic flows. Such nonlinear properties cannot be affected by payload encryption or dynamic port change and hence cannot be easily masqueraded. In performing a quantitative assessment of the above transition patterns, we used recurrence quantification analysis, a nonlinear technique widely used in many fields of science to discover the time correlations and the hidden dynamics of statistical time series. Our model proved to be effective for providing a deterministic interpretation of recurrence patterns derived by complex protocol dynamics in end-to-end traffic flows, and hence for developing qualitative and quantitative observations that can be reliably used in traffic classification.