BLINC: multilevel traffic classification in the dark
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
OpenFlow: enabling innovation in campus networks
ACM SIGCOMM Computer Communication Review
A comparative study of different heavy tail index estimators of the flow size from sampled data
Proceedings of the first international conference on Networks for grid applications
TIE: A Community-Oriented Traffic Classification Platform
TMA '09 Proceedings of the First International Workshop on Traffic Monitoring and Analysis
On dominant characteristics of residential broadband internet traffic
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
Semantic security against web application attacks
Information Sciences: an International Journal
Traffic pattern based virtual network embedding
Proceedings of the 2013 workshop on Student workhop
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The fast changing application types and their behavior require consecutive measurements of access networks. In this paper, we present the results of a 14-day measurement in an access network connecting 600 users with the Internet. Our application classification reveals a trend back to HTTP traffic, underlines the immense usage of flash videos, and unveils a participant of a Botnet. In addition, flow and user statistics are presented, which resulting traffic models can be used for simulation and emulation of access networks.