Understanding Internet Censorship in Europe: The Case of Spain

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Abstract

European Union (EU) member states consider themselves bulwarks of democracy and freedom of speech. However, there is a lack of empirical studies assessing possible violations of these principles in the EU through Internet censorship. This work starts addressing this research gap by investigating Internet censorship in Spain over 2016-2020, including the controversial 2017 Catalan independence referendum. We focus, in particular, on network interference disrupting the regular operation of Internet services or contents. We analyzed the data collected by the Open Observatory of Network Interference (OONI) network measurement tool. The measurements targeted civil rights defending websites, secure communication tools, extremist political content, and information portals for the Catalan referendum. Our analysis indicates the existence of advanced network interference techniques that grow in sophistication over time. Internet Service Providers (ISPs) initially introduced information controls for a clearly defined legal scope (i.e., copyright infringement). Our research observed that such information controls had been re-purposed (e.g., to target websites supporting the referendum). We present evidence of network interference from all the major ISPs in Spain, serving 91% of mobile and 98% of broadband users and several governmental and law enforcement authorities. In these measurements, we detected 16 unique blockpages, 2 Deep Packet Inspection (DPI) vendors, and 78 blocked websites. We also contribute an enhanced domain testing methodology to detect certain kinds of Transport Layer Security (TLS) blocking that OONI could not initially detect. In light of our experience analyzing this dataset, we also make suggestions on improving the collection of evidence of network interference.

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APA

Ververis, V., Ermakova, T., Isaakidis, M., Basso, S., Fabian, B., & Milan, S. (2021). Understanding Internet Censorship in Europe: The Case of Spain. In ACM International Conference Proceeding Series (pp. 319–328). Association for Computing Machinery. https://doi.org/10.1145/3447535.3462638

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