Abstract
Classifying traffic is an important task for effective network planning and design, and monitoring the trends of the applications in operational networks. In this paper, we propose flow traffic classification methods using support vector machine. Classifying traffic is an important task for effective network planning and design, and monitoring the trends of the applications in operational networks. The proposals satisfy the following three requirements. Using to only flow information, not using port numbers, automatic making of traffic models. In this paper, we provide an empirical evaluation of our proposals using datasets of MIT Lincoln Laboratory, which illustrates that our proposals can classify network traffic flow over 90 % precision.
Original language | English |
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Title of host publication | Proceedings of the 2009 2nd International Conference on Computer Science and Its Applications, CSA 2009 |
DOIs | |
Publication status | Published - Dec 1 2009 |
Event | 2009 2nd International Conference on Computer Science and Its Applications, CSA 2009 - Jeju Island, Korea, Republic of Duration: Dec 10 2009 → Dec 12 2009 |
Other
Other | 2009 2nd International Conference on Computer Science and Its Applications, CSA 2009 |
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Country/Territory | Korea, Republic of |
City | Jeju Island |
Period | 12/10/09 → 12/12/09 |
All Science Journal Classification (ASJC) codes
- Computational Theory and Mathematics
- Computer Science Applications