Our presentation delves into the innovative integration of Differential Privacy (DP) and Secure Multiparty Computation (MPC) to develop advanced PETs for ad measurement. Our technology tackles the critical challenges of preserving user privacy in advertising by preventing advertisers and publishers from tracking users' activities across platforms. This approach not only safeguards user privacy but also enables valuable ad measurement insights, benefiting both advertisers and publishers.
Jian Du
Jian Du is a research scientist at TikTok, leading the research and development efforts focused on integrating privacy-enhancing technologies into TikTok's products. For instance, Jian leads the development of PrivacyGo, an open-source project available on GitHub. Privacy Go aims to synergistically fuse PETs to address real-world privacy challenges, such as combining secure multi-party computation and differential privacy to enable privacy-preserving ad measurement and optimization of ad models, as well as privacy-preserving large language models. Prior to joining TikTok, Jian worked on PETs at Ant Financial and held a postdoctoral research position at Carnegie Mellon University.