We present C-Saw, a system that measures Internet censorship by offering data-driven censorship circumvention to users. The adaptive circumvention capability of C-Saw incentivizes users to opt-in by offering small page load times (PLTs). As users crowdsource, the measurement data gets richer, offering greater insights into censorship mechanisms over a wider region, and in turn leading to even better circumvention capabilities. C-Saw incorporates user consent in its design by measuring only those URLs that a user actually visits. Using a cross-platform implementation of C-Saw, we show that it is effective at collecting and disseminating censorship measurements, selecting circumvention approaches, and optimizing user experience. C-Saw improves the average PLT by up to 48% and 63% over Lantern and Tor, respectively. We demonstrate the feasibility of a large-scale deployment of C-Saw with a pilot study.

Existing research on Internet censorship primarily focuses on either measurements or circumvention. Considering these two in isolation often leads to designs with limited capabilities: Circumvention is not driven by measurement data and end users find little incentive to help gather such data. We present the preliminary design and implementation of C-Saw, a platform that offers both. The circumvention capability of C-Saw incentivizes consumers to opt-in. As more and more consumers crowdsource, the monitoring data gets richer. This, in turn, offers greater insights into the censorship mechanisms over a wider region, offering even better circumvention capabilities. C-Saw is a browser-based platform set up as a lightweight client-side proxy. C-Saw adapts its circumvention approach to the particular censorship mechanism deployed by a user's ISP, achieving a better balance of circumvention effectiveness and performance. In addition, it can also leverage the heterogeneity in filtering mechanisms across ISPs to achieve better circumvention performance. We demonstrate this using page load times across various ISPs and locations in a censored region. Unlike previous measurement approaches, C-Saw does not require the knowledge of a target URL to be tested. In fact, as URLs get blocked, their information can be monitored in real time.