CensMon: A Web Censorship Monitor
Elias Athanasopoulos, Sotiris Ioannidis, Andreas Sfakianakis · Foundations of Computational Intelligence · 2011
The Internet has traditionally been the most free medium for publishing and accessing information. It is also quickly becoming the dominant medium for quick and easy access to news. It is therefore not surprising that there are significant efforts to censor certain news articles or even entire web sites. For this reason, it is paramount to try to detect what is censored and by whom. In this paper we present the design and implemention of a web censorship monitor, called CensMon. CensMon is distributed in nature, operates automatically and does not rely on Internet users to report censored web sites, can differentiate access network failures from possible censorship, and uses multiple input streams to determine what kind of censored data to look for. Our evaluation shows that CensMon can successfully detect censored content and spot the filtering technique used by the censor.