Automated Detection and Fingerprinting of Censorship Block Pages
Automated Detection and Fingerprinting of Censorship Block Pages
复制标题
审查封锁页面的自动检测和指纹识别
DOI：
10.1145/2663716.2663722
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Phillipa Gill
中科院分区：
文献类型：
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作者：
Ben Jones;Tzu;N. Feamster;Phillipa Gill
强制执行Web审查的一种方法是返回一个阻止页面，通知用户访问网页的尝试不成功。检测阻止页面可以提供更完整的Web审查情况，但自动识别阻止页面是困难的，因为Web内容是动态的，个性化的，甚至可能是不同的语言。以前的工作是人工检测和识别块页，这很难复制;这也很耗时，这使得很难对审查进行连续的纵向研究。本文提出了一种自动化的方法来检测块页面和指纹的过滤产品，产生他们。我们的自动化方法可以连续测量块页面;我们发现，我们的方法成功地检测到95%的块页面，并确定了五个过滤工具，包括一个以前没有被确定为“在野外”的工具。
One means of enforcing Web censorship is to return a block page, which informs the user that an attempt to access a webpage is unsuccessful. Detecting block pages can provide a more complete picture of Web censorship, but automatically identifying block pages is difficult because Web content is dynamic, personalized, and may even be in different languages. Previous work has manually detected and identified block pages, which is difficult to reproduce; it is also time-consuming, which makes it difficult to perform continuous, longitudinal studies of censorship. This paper presents an automated method both to detect block pages and to fingerprint the filtering products that generate them. Our automated method enables continuous measurements of block pages; we found that our methods successfully detect 95% of block pages and identify five filtering tools, including a tool that had not been previously identified "in the wild".