Title : Internet Traffic Classification Demystified: Myths, Caveats, and the Best Practices.
Speaker : 김현철 (Hyun-chul Kim, )
Date : 2008.4.4 (금) 14:00 – 15:00
Place : 301동 520호
Abstract :
Recent research on Internet traffic classification algorithms has yield a flurry of
proposed approaches for distinguishing types of traffic, but no systematic
comparison of the various algorithms. This fragmented approach to
traffic classification research leaves the operational community
with no basis for consensus on what approach to use when,
and how to interpret results. In this work we critically revisit traffic
classification by conducting a thorough evaluation of three
classification approaches, based on transport layer ports,
host behavior (BLINC), and flow features (machine learning algorithms).
A strength of our work is the broad range of data against which
we test the three classification approaches: seven traces with payload
collected in Japan, Korea, and US. The diverse geographic locations,
link characteristics and application traffic mix in these data allowed us
to evaluate the approaches under a wide variety of conditions.
We analyze the advantages and limitations of each approach,
evaluate methods to overcome the limitations, and extract insights
and recommendations for both the study and practical application of traffic classification.
We make our software, classifiers, and data available for researchers interested in validating or extending this work.
약력:
2008. Mar~ : BK 계약조교수, 서울대학교 컴퓨터공학부
2006.Jan ~ 2007.Dec. : Postdoctoral visiting scholar, CAIDA, SDSC/UC San Diego
2005.May~ 2005.Dec. : 연구교수, ICU 공학부
2005.Mar.~2005.Apr. : 박사후연구원, KAIST 전자전산학부
2005.Feb. : 박사, KAIST 전자전산학부
1997.Aug. : 석사, KAIST 전산학과
1995.Feb. : 학사, KAIST 전산학과