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.

liberate
liberate, a general-purpose tool for automatically identifying middlebox policies, reverse-engineering their implementations, and adaptively deploying custom circumvention techniques. liberate conducts targeted network measurements to identify the corresponding inconsistencies and leverages this information to transform arbitrary network traffic such that it is purposefully misclassified (e.g., to avoid shaping or censorship).

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. 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.

Email: . If you are on campus, you can probably find me in the office ISEC 6th floor.