Can censorship measurements be safe(r)?

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Abstract

Understanding censorship requires performing widespread, continuous measurements "on the ground". Yet, measuring censorship is potentially dangerous, due to the threat of retaliation against citizens who perform measurements. We must balance measurement accuracy, reliability, and scalability with user safety which leads us to the question: Can we design censorship measurements that mitigate risk to the users who consent to perform them? Although it is almost certainly impossible to eliminate risk (or even determine if we have succeeded in doing so), we posit that we may be able to reduce risk with measurement techniques that are difficult to observe or distinguish from innocuous network activity. We observe that surveillance and censorship systems have different goals, and thus certain types of measurement techniques may be able to characterize a censorship system without triggering a surveillance system. We design and implement several techniques for measuring censorship that controlled tests suggest might be less risky than existing methods; we also highlight potential pitfalls, limitations, and avenues for future work.

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APA

Jones, B., & Feamster, N. (2015). Can censorship measurements be safe(r)? In Proceedings of the 14th ACM Workshop on Hot Topics in Networks, HotNets-XIV 2015. Association for Computing Machinery, Inc. https://doi.org/10.1145/2834050.2834066

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