Fangfan Li

李方帆

PhD student in Computer Science


I am a third-year computer science PhD student at Northeastern University, advised by David Choffnes. I have a broad interest in understanding the Internet and improving the user experience. Recently, I have been working on identifying traffic differentiation, how network traffic are classified and possible ways to avoid being classified.

Before joining Northeastern, I received my M.S. in Computer Engineering at Duke University (Let's go Blue Devils!) , and spent four amazing years completing my B.S. in Electronic Engineering at UESTC, ChengDu, China.

Classifiers Unclassified
In this work, we develop a general approach for identifying classification rules (i.e., the network provider's "educated guesses") that map network traffic to applications. Specifically, we use an efficient binary search and carefully-generated network flows to minimize the number of testes needed to reverse engineer the rules. We also characterize the classification rules for HTTP(S) traffic implemented in today's carrier-grade middleboxes and identify examples of misclassification (traffic from application A being labeled mistakenly as application B). In summary, our analysis shows that different vendors use different matching rules, but all generally focus on a small number of fields inside HTTP/S traffic. used binary search and carefully-generated flows to eliminate the number of tests to run for reverse-engineering the rules.

Email: . If you are on campus, you can probably find me in the office ISEC 4th floor.