Measuring the Deployment of Network Censorship Filters at Global Scale
Measuring the Deployment of Network Censorship Filters at Global Scale
复制标题
衡量全球范围内网络审查过滤器的部署
DOI：
10.14722/ndss.2020.23099
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Roya Ensafi
中科院分区：
文献类型：
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作者：
R. Raman;Adrian Stoll;Jakub Dalek;Reethika Ramesh;W. Scott;Roya Ensafi
-内容fi技术经常用于互联网审查，但即使这些技术已经变得更便宜、更容易部署，审查测量界也缺乏系统的方法来监测它们的扩散。过去的研究集中在少数几种特定的ficfi检测技术上，每一种技术都需要繁琐的人工检测工作才能识别。研究人员和政策制定者需要更全面地了解基于内容fi的审查制度的状态和演变，以便制定保护互联网自由的有效政策。在这项工作中，我们提出了一种新的框架FilterMap，它可以基于内容块页面来可扩展地监控内容fi技术。FilterMapfiRST汇编了网络内和新的远程审查测量技术，以从fi以后的部署中收集块页。然后，我们展示了如何对观察到的块页面进行集群，生成用于纵向跟踪的签名。FilterMap输出出现相同块页的地址空间区域的映射(对应于fi后部署)，并且手动验证每个唯一的块页以避免误报。通过收集和分析来自18,000多个敏感测试域的45,000个有利位置的3.79亿多个测量数据，我们能够识别与90个供应商和参与者相关的filter部署，并观察103个国家/地区的fi测试。我们发现，在被自由之家“网络自由”报告标记为“非自由”或“部分自由”的48个国家中，有36个国家使用了商业fi技术进行审查。内容fi加密技术的不受限制的传输导致了高可用性、低成本和高效的fi加密技术变得更容易部署和更难规避。识别这些fi排放部署突出了政策和企业社会责任问题，并增加了对fi排放制造商的责任。我们继续发布FilterMap数据将帮助国际社会跟踪基于内容的审查的范围、规模和演变。
—Content filtering technologies are often used for Internet censorship, but even as these technologies have become cheaper and easier to deploy, the censorship measurement community lacks a systematic approach to monitor their proliferation. Past research has focused on a handful of specific filtering technologies, each of which required cumbersome manual detective work to identify. Researchers and policymakers require a more comprehensive picture of the state and evolution of censorship based on content filtering in order to establish effective policies that protect Internet freedom. In this work, we present FilterMap, a novel framework that can scalably monitor content filtering technologies based on their blockpages. FilterMap first compiles in-network and new remote censorship measurement techniques to gather blockpages from filter deployments. We then show how the observed blockpages can be clustered, generating signatures for longitudinal tracking. FilterMap outputs a map of regions of address space in which the same blockpages appear (corresponding to filter deployments), and each unique blockpage is manually verified to avoid false positives. By collecting and analyzing more than 379 million measurements from 45,000 vantage points against more than 18,000 sensitive test domains, we are able to identify filter deployments associated with 90 vendors and actors and observe filtering in 103 countries. We detect the use of commercial filtering technologies for censorship in 36 out of 48 countries labeled as ‘Not Free’ or ‘Partly Free’ by the Freedom House “Freedom on the Net” report. The unrestricted transfer of content filtering technologies have led to high availability, low cost, and highly effective filtering techniques becoming easier to deploy and harder to circumvent. Identifying these filtering deployments highlights policy and corporate social responsibility issues, and adds accountability to filter manufacturers. Our continued publication of FilterMap data will help the international community track the scope, scale and evolution of content-based censorship.