Abstract This paper considers online news censorship and it concentrates on censorship of identities. Obfuscating identities may occur for disparate reasons, from military to judiciary ones. In the majority of cases, this happens to protect individuals from being identified and persecuted by hostile people. However, being the collaborative web characterised by a redundancy of information, it is not unusual that the same fact is reported by multiple sources, which may not apply the same restriction policies in terms of censorship. Also, the proven aptitude of social network users to disclose personal information leads to the phenomenon that comments to news can reveal the data withheld in the news itself. This gives us a mean to figure out who the subject of the censored news is. We propose an adaptation of a text analysis approach to unveil censored identities. The approach is tested on a synthesised scenario, which however resembles a real use case. Leveraging a text analysis based on a context classifier trained over snippets from posts and comments of Facebook pages, we achieve promising results. Despite the quite constrained settings in which we operate – such as considering only snippets of very short length – our system successfully detects the censored name, choosing among 10 different candidate names, in more than 50 of the investigated cases. This outperforms the results of two reference baselines. The findings reported in this paper, other than being supported by a thorough experimental methodology and interesting on their own, also pave the way for further investigation on the insidious issues of censorship on the web.
@cite_18: 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.
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@cite_15: The public perceives the Web as a wildly uncensored medium, the embodiment of complete freedom of expression (for good or bad). In reality, information on the Web is not as uncontrolled as it may appear. According to the OpenNet Initiative (www.opennet.net), more than 40 countries actively filter Web access- selectively blocking content to a billion Internet users worldwide-and many others are considering doing so. These countries use various methods to apply different levels of filtering.
@cite_16: Over the years, the Internet has democratized the flow of information. Unfortunately, in parallel, authoritarian regimes and other entities (such as ISPs) for their vested interests have curtailed this flow by partially or fully censoring the web. The policy, mechanism, and extent of this censorship varies from country to country. We present the first study of the cause, effect, and mechanism of web censorship in Pakistan. Specifically, we use a publicly available list of blocked websites and check their accessibility from multiple networks within the country. Our results indicate that the censorship mechanism varies across websites: some are blocked at the DNS level while others at the HTTP level. Interestingly, the government shifted to a centralized, Internet exchange level censorship system during the course of our study, enabling our findings to compare two generations of blocking systems. Furthermore, we report the outcome of a controlled survey to ascertain the mechanisms that are being actively employed by people to circumvent censorship. Finally, we discuss some simple but surprisingly unexplored methods of bypassing restrictions.
@cite_10: In this study, we take another look at 5 years of web censorship data gathered by the OpenNet Initiative in 77 countries using user-based testing with locally relevant content. Prior to our work, this data had been analyzed with little automation, focusing on what content had been blocked, rather than how blocking was carried out. In this study, we use more rigorous automation to obtain a longitudinal, global view of the technical means used for web censorship. We also identify blocking that had been missed in prior analyses. Our results point to considerable variability in the technologies used for web censorship, across countries, time, and types of content, and even across ISPs in the same country. In addition to characterizing web censorship in countries that, thus far, have eluded technical analysis, we also discuss the implications of our observations on the design of future network measurement platforms and circumvention technologies.
@cite_12: While mechanics of Web censorship in China are well studied, those of other countries are less understood. Through a combination of personal contacts and Planet-Lab nodes, we conduct experiments to explore the mechanics of Web censorship in 11 countries around the world, including China. Our work provides insights into the diversity of modus operandi of censors around the world and can guide future work on censorship evasion.
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For the sake of completeness, we acknowledge the occurrence of different kinds of censorship, from DNS to router level ones @cite_12 . Differently from veiling single terms, an entire domain might not be accessible, thus requiring different approaches to circumvent the block @cite_15 . Work in @cite_10 @cite_28 @cite_24 propose a survey on different topics related to censorship, either on detection or possible countermeasures. Also, monitoring tools exist, to trace the diffusion of the phenomenon @cite_16 @cite_18 . Finally, emails or other communication channels different from social media might be affected by censorship @cite_17 .