Net neutrality, or the notion that Internet service providers (ISPs) are not giving equal services to different parties, has been discussed actively over the last few years. Wehe is a large-scale, longitude empirical study of ISPs’ traffic management policies that violate net neutrality principles.
Expectation: Given that the Wehe dataset is collected from the large-scale and longitude empirical study, it is not feasible to display the raw data without a proper visualization. This visualization project is trying to provide an interactive, focused visualization to help individual users to understand the meaning of the data.
Wehe uses your device to exchange Internet traffic recorded from real, popular apps like YouTube and Spotify---effectively making it look as if you are using those apps. As a result, if an Internet service provider (ISP) tries to slow down YouTube, Wehe would see the same behavior. We then send the same app's Internet traffic, but replacing the content with randomized bytes, which prevents the ISPs from classifying the traffic as belonging to the app. Our hypothesis is that the randomized traffic will not cause an ISP to conduct application-specific differentiation (e.g., throttling or blocking), but the original traffic will. We repeat these tests several times to rule out noise from bad network conditions, and tell you at the end whether your ISP is giving different performance to an app's network traffic.
In Wehe dataset, each datapoint demonstrates whether or not the current setup has detected differentiation (which has multiple runs and is classified by statistical testing). For every datapoint, it records the time when the test was conducted, where the test was conducted, which ISP was the service provider and what application it tested with.