At this year’s 5th Ad Filtering Dev Summit, several ProperData members presented the latest on ad filtering technologies and online privacy projects, both in person in Amsterdam and remotely.
Graduate student Hieu Le (UC Irvine) presented his work on AutoFR, an automated filter rule generator using reinforcement learning for ad blocking. Graduate student Shaoor Munir (UC Davis) presented COOKIEGRAPH, a machine learning approach that can accurately predict whether first party cookies are used for tracking purposes. Collaborator and post doc Umar Iqbal (University of Washington) presented his work on a purpose built approach to protect against advertising and tracking request chains. Graduate student Abdul Haddi Amjad (Virginia Tech University) presented his work on automated fault localization techniques that can be used to build the next generation of content blockers.
We are glad to have our graduate students disseminate their findings in the goal of informing the public, software developers and other relevant stakeholders in the ad-filtering tech community.
Additional information on the summit can be found here.
See all papers and work on our publications page.