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The project develops new technologies for continual, web-scale measurement and rapid defenses against emerging threats to web privacy and security arising from third-party tracking. It draws from the fields of web security, systems, measurement, statistics, and machine learning. The outputs of this project will enable website administrators to find and fix a large class of privacy and security problems. They will help improve existing browser privacy tools. Finally, they will aid regulatory enforcement and contribute to better-informed press reporting on online privacy and security.
This project is driven by two fundamental questions: (i) which privacy and security threats are created or exacerbated by the presence of embedded third party elements? and (ii) how can we automatically detect these problems and develop defensive tools for users and site administrators? The project uses automated web browsing and measurement to generate "third-party threat profiles" for websites, maintain a "web privacy census," and develop a new class of browser privacy tools using machine learning. The project brings transparency to the third-party ecosystem and enables oversight, giving users and developers the upper hand in blocking unwanted tracking and supporting enforcement actions when companies violate established privacy rules.
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TWC: Small: Online tracking: Threat Detection, Measurement and Response