FilteredWeb: A framework for the automated search-based discovery of blocked URLs
Various methods have been proposed for creating and maintaining lists of potentially filtered URLs to allow for measurement of ongoing internet censorship around the world. Whilst testing a known resource for evidence of filtering can be relatively simple, given appropriate vantage points, discovering previously unknown filtered web resources remains an open challenge. Authors present a novel framework for automating the process of discovering filtered resources through the use of adaptive queries to well-known search engines. Implementation of this framework, applied to China as a case study, shows the approach is demonstrably effective at detecting significant numbers of previously unknown filtered web pages, making a significant contribution to the ongoing detection of internet filtering as it develops.
Darer, A, Farnan, O and Wright, J et al., (2017). FilteredWeb: A framework for the automated search-based discovery of blocked URLs. 2017 Network Traffic Measurement and Analysis Conference (TMA). https://ora.ox.ac.uk/objects/uuid:6321b48a-9a84-4452-8e2b-9e0ccb59ff67
Published: Apr 2017 | Categories: Research Articles
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