This project studies Internet censorship using novel measurement techniques, ranging from low-level packet filtering on Internet Protocol (IP) networks to high-level censorship of social media content. Collectively these techniques can provide greater situational awareness of censorship dynamics.
The project focuses on a suite of advanced inference techniques for when ?direct observation? is unavailable or impractical such as, for example, methods for detecting IP tunnels based on per-hop Maximum Transmission Unit (MTU) inference techniques in order to reason about the physical characteristics of a given IP network and, for example, measurement on social media postings of redactions and the speed of redactions.
This research has broad implications on studies of methods to provide awareness of restrictive control of information and content on networks, which would be of interest to software developers, system administrators, and policy makers alike.
