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Meta enforces purpose limitation via Privacy Aware Infrastructure at scale
At Meta, we’ve been diligently working to incorporate privacy into different systems of our software stack over the past few years. Today, we’re excited to share some cutting-edge techn…
It conducts runtime evaluation of constraints, context propagation, and is deeply integrated with numerous data and code frameworks (e.g., HHVM, Presto, and Spark), representing a step change in how we approach information flow control. However, we realized that our designs for function-based systems were quite abstract and the adoption for a large-scale use case resulted in significant challenges, consequently, requiring considerable effort to map patterns to customer needs. In particular, we would like to extend special thanks to (in alphabetical order) Adrian Zgorzalek, Alex Gorelik, Amritha Raghunath, Anuja Jaiswal, Brian Sniffen, Brian Romanko, Brian Spanton, David Detlefs, David Mortenson, David Taieb, Gabriela Jacques da Silva, Ian Carmichael, Iuliu Rus, Jafar Husain, Jerry Pan, Jiang Wu, Joel Krebs, Jun Fang, Komal Mangtani, Marc Celani, Mark Konetchy, Michael Levin, Perry Stoll, Peter Prelich, Pieter Viljoen, Prashant Dhamdhere, Rajesh Nishtala, Rajkishan Gunasekaran, Rishab Mangla, Sergey Doroshenko, Seth Silverman, Sriguru Chakravarthi, Tarek Sheasha, Thomas Georgiou, Uday Ramesh Savagaonkar, Vitalii Tsybulnyk, Vlad Fedorov, Wolfram Schulte, and Yi Huang.
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