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A Secure and Private Platform for Transparent Research Access via Trusted Execution Environments

June 6, 4:05 PM - 4:25 PM
Imperial Room A

The recent shift in regulatory demands, which are aimed at fostering an understanding of the systemic risks, is pushing large online platforms and search engines towards greater transparency. Some regulations require these companies to grant privileged data access to vetted researchers. However, this could potentially lead to unintentional misuse or leaks of user privacy. It is very hard, yet important, to design a platform that strives to balance transparency with robust protections to mitigate these privacy risks. This session will discuss a solution that leverages trusted execution environments (TEEs) in the cloud to balance between transparency and user privacy. We demonstrate how TEEs can provide data confidentiality and execution integrity to both data owners and data scientists. We will also discuss future opportunities and other use cases of the solution.

About the speakers

Dayeol Lee

Research Scientist, TikTok

Dayeol Lee is currently a research scientist at TikTok's Privacy Innovation Lab. His research interests are system security, trusted computing, and computer architecture. He earned his Ph.D. in Electrical Engineering and Computer Sciences from the University of California, Berkeley, where he studied computer systems and security. Dayeol holds a BS and an MS in Computer Science and Engineering from Pohang University of Science and Technology.

Mingshen Sun

Research Scientist, TikTok

Mingshen Sun is a research scientist at TikTok, leading applications and innovations of trusted & confidential computing technologies. He also serves on PPMC of the Apache Teaclave (incubating) project.