Algorithms for clustering data
Algorithms for clustering data
Fast accurate computation of large-scale IP traffic matrices from link loads
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
An Analysis of Internet Inter-Domain Topology and Route Stability
INFOCOM '97 Proceedings of the INFOCOM '97. Sixteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Driving the Information Revolution
Automatically inferring patterns of resource consumption in network traffic
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Estimating flow distributions from sampled flow statistics
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Sketch-based change detection: methods, evaluation, and applications
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Flow classification by histograms: or how to go on safari in the internet
Proceedings of the joint international conference on Measurement and modeling of computer systems
Flow sampling under hard resource constraints
Proceedings of the joint international conference on Measurement and modeling of computer systems
The impact of BGP dynamics on intra-domain traffic
Proceedings of the joint international conference on Measurement and modeling of computer systems
Diagnosing network-wide traffic anomalies
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
Aberrant Behavior Detection in Time Series for Network Monitoring
LISA '00 Proceedings of the 14th USENIX conference on System administration
Internet traffic classification using bayesian analysis techniques
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
A data streaming algorithm for estimating subpopulation flow size distribution
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
Mining anomalies using traffic feature distributions
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
Understanding Patterns of TCP Connection Usage with Statistical Clustering
MASCOTS '05 Proceedings of the 13th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems
Automated Traffic Classification and Application Identification using Machine Learning
LCN '05 Proceedings of the The IEEE Conference on Local Computer Networks 30th Anniversary
Entropy Based Worm and Anomaly Detection in Fast IP Networks
WETICE '05 Proceedings of the 14th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprise
Robust traffic matrix estimation with imperfect information: making use of multiple data sources
SIGMETRICS '06/Performance '06 Proceedings of the joint international conference on Measurement and modeling of computer systems
Understanding the network-level behavior of spammers
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
Traffic classification using clustering algorithms
Proceedings of the 2006 SIGCOMM workshop on Mining network data
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
Combining filtering and statistical methods for anomaly detection
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
Detecting anomalies in network traffic using maximum entropy estimation
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
An empirical evaluation of entropy-based traffic anomaly detection
Proceedings of the 8th ACM SIGCOMM conference on Internet measurement
Fast monitoring of traffic subpopulations
Proceedings of the 8th ACM SIGCOMM conference on Internet measurement
Internet traffic behavior profiling for network security monitoring
IEEE/ACM Transactions on Networking (TON)
A nonlinear, recurrence-based approach to traffic classification
Computer Networks: The International Journal of Computer and Telecommunications Networking
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems
Routing demands with time-varying bandwidth profiles on a MPLS network
Computer Networks: The International Journal of Computer and Telecommunications Networking
Traffic matrix reloaded: impact of routing changes
PAM'05 Proceedings of the 6th international conference on Passive and Active Network Measurement
Self-Learning IP traffic classification based on statistical flow characteristics
PAM'05 Proceedings of the 6th international conference on Passive and Active Network Measurement
A parameterizable methodology for Internet traffic flow profiling
IEEE Journal on Selected Areas in Communications
Catching popular prefixes at AS border routers with a prediction based method
Computer Networks: The International Journal of Computer and Telecommunications Networking
Review: A survey of network flow applications
Journal of Network and Computer Applications
Information Sciences: an International Journal
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A cardinal prerequisite for the proper and efficient management of a network, especially an ISP network, is to understand the traffic that it carries. Traffic profiling is a means to obtain knowledge of the traffic behavior. Previous work has been focusing on traffic profiling at the link level or the host level. However, network prefix-level traffic behaviors have not yet been investigated. In this paper, we are interested in empirical studies for finding and describing structural patterns in the overwhelming network measurement data, as well as obtaining insight from it, with the expected traffic profiles potentially of interest to a broad range of applications such as network management, traffic engineering, and data services. To this end, first, we derive a collection of features that characterize the network prefix-level aggregate traffic behaviors. Next we use a simple model to capture them on all features, and apply machine learning techniques to extract representative profiles from them. Finally, we collect Netflow measurements from the entire periphery of a Tier-1 ISP network to empirically validate the simple model we proposed. Our extensive results show that nearly all networks exhibit traffic characteristics that are stable over time. The derived traffic profiles provide valuable insights on the manifold behavioral patterns that cannot be easily learned otherwise.