ICLab has been operated continuously since late 2016. It achieves a new balance between breadth of coverage and detail of measurements, by using commercial VPNs as vantage points distributed around the world. In this work, we present ICLab, an Internet measurement platform specialized for censorship research. Collecting enough data for a comprehensive, global, longitudinal perspective remains challenging. 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 breadth of coverage. Researchers have studied Internet censorship for nearly as long as attempts to censor contents have taken place. Latent feature representations likely encode more nuances in the data since the latent feature learning approach discovers a greater quantity, and a more diverse set, of new censorship instances. Both classification models are capable of detecting network-based Internet censorship as we were able to identify instances of censorship not detected by the known fingerprints. We compare and evaluate both approaches using data sets from Censored Planet via a hold-out evaluation. Our image-based classification model encodes a network reachability data record as a gray-scale image and classifies the image as censored or not using a dense convolutional neural network. To estimate the probability of censorship events from the inferred latent features, we rely on a densely connected multi-layer neural network model. To infer latent feature representations from network reachability data, we propose a sequence-to-sequence autoencoder to capture the structure and the order of data elements in the data. Seeking to overcome these challenges, we design and evaluate a classification model based on latent feature representation learning and an image-based classification model to detect network-based Internet censorship. While this rule-based approach yields a high true positive detection rate, it suffers from several challenges: it requires human expertise, is laborious, and cannot detect any censorship not captured by the rules. However, existing studies generally rely on manually designed rules (i.e., using censorship fingerprints) to detect network-based Internet censorship from the data. Several research groups, such as Censored Planet, have deployed large scale Internet measurement platforms to collect network reachability data. Internet censorship is a phenomenon of societal importance and attracts investigation from multiple disciplines. In light of our experience analyzing this dataset, we also make suggestions on improving the collection of evidence of network interference. 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 these measurements, we detected 16 unique blockpages, 2 Deep Packet Inspection (DPI) vendors, and 78 blocked websites. 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. Our research observed that such information controls had been re-purposed (e.g., to target websites supporting the referendum). Internet Service Providers (ISPs) initially introduced information controls for a clearly defined legal scope (i.e., copyright infringement). Our analysis indicates the existence of advanced network interference techniques that grow in sophistication over time. The measurements targeted civil rights defending websites, secure communication tools, extremist political content, and information portals for the Catalan referendum. We analyzed the data collected by the Open Observatory of Network Interference (OONI) network measurement tool. We focus, in particular, on network interference disrupting the regular operation of Internet services or contents. This work starts addressing this research gap by investigating Internet censorship in Spain over 2016-2020, including the controversial 2017 Catalan independence referendum. However, there is a lack of empirical studies assessing possible violations of these principles in the EU through Internet censorship. European Union (EU) member states consider themselves bulwarks of democracy and freedom of speech.
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