Lead PI

• David Choffnes

Co PI

• Alan Mislove

Abstract

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 an 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.

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Funding

NSF

Related Publications

• Fangfan Li, Arian Niaki, David Choffnes, Phillipa Gill, Alan Mislove. “A large-scale analysis of deployed traffic differentiation practices.” Proceedings of the ACM Special Interest Group on Data Communication. 2019. 130-144. DOI: 10.1145/3341302.3342092
• Arash Molavi Kakhki, Abbas Razaghpanah, Hyungjoon Koo, Anke Li, Rajeshkumar Golani, David Choffnes, Phillipa Gill, and Alan Mislove. “Identifying traffic differentiation in mobile networks.” Proceedings of the 2015 Internet Measurement Conference. 2015. DOI: 10.1145/2815675.2815691