Privacy Policies and Measurement - First introduced as a way of recording client-side state, third-party vendors have proliferated widely on the Web, and have become a fundamental part of the Web ecosystem. However, there is widespread concern that third-party vendors are being abused to track and profile individuals online for commercial, analytical and various other purposes. This paper builds the platform called “PRIVIS”, aiming at providing unique insights on how the privacy ecosystem is structured and affected through the analysis of data that stems from real users. First, to showcase what can be learned from this ecosystem through a datadriven analysis across the country, time and first-party categories, PRIVIS visualises data gathered from over 10K Chrome installers. It also equips participants with the means to collect and analyze their own data so that they could assess how their browsing habits are shared with third parties from their perspectives. Based on real-user datasets, the third-party quantity is not the only measure of web privacy risks. The measure proposed in this paper is how well thirdparty providers know their users. Second, PRIVIS studies the interplay between user location, special periods (after epidemic outbreak) and the overall number of third parties observed. The visualisation suggests that lockdown policies facilitate the growth in the number of third parties. Collectively, there are more active third-party activities, compared with both before the lockdowns and the corresponding periods in the previous year. And throughout the lockdown stages, the first lockdown performs the most aggressive.

jul

Fuzhou, China

https://ieeexplore.ieee.org/document/9862682/