censorship measurement

Augmenting Rule-based DNS Censorship Detection at Scale with Machine Learning

Abstract: The proliferation of global censorship has led to the development of a plethora of measurement platforms to monitor and expose it. Censorship of the domain name system (DNS) is a key mechanism used across different countries. It is currently detected by applying heuristics to samples of DNS queries and responses (probes) for specific destinations. These heuristics, however, are both platform-specific and have been found to be brittle when censors change their blocking behavior, necessitating a more reliable automated process for detecting censorship.

ICLab: A Global, Longitudinal Internet Censorship Measurement Platform

Researchers have studied Internet censorship for nearly as long as attempts to censor contents have taken place. Most studies have however been limited to a short period of time and/or a few countries; the few exceptions have traded off detail for …

Measuring I2P Censorship at a Global Scale

The prevalence of Internet censorship has prompted the creation of several measurement platforms for monitoring filtering activities. An important challenge faced by these platforms revolves around the trade-off between depth of measurement and …