Deployments Meta Private Lift Measurement for Private Advertising
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Meta Private Lift Measurement for Private Advertising

Meta’s Private Lift Measurement uses MPC to allow both Meta and an advertiser to learn insights about how an ad is performing without the need to trust either party with both datasets. MPC limits the information that can be learned by either Meta or the advertiser.

Code

GitHub - facebookresearch/fbpcs: FBPCS (Facebook Private Computation Solutions)

GitHub - facebookresearch/fbpcf: Private computation framework library

Meta: The Value of Secure Multi-Party Computation

Meta: Privacy-Enhancing Technologies and Building for the Future

Meta: What Are Privacy-Enhancing Technologies (PETs) and How Will They Apply to Ads?

Presentation

Slides: Real World Crypto 2022

This post is licensed under CC BY 4.0 by the author.

In recent years, MPC (secure multi-party computation) has seen an increase in adoption in real-world use cases. Find deployments here and add more.


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