USENIX Lightning Talk: Fully decentralized auditable framework for privacy-preserving aggregation

Our framework can aggregate validated user-provided data without exposing their privacy


In this talk, we introduce Kaires, a fully decentralized aggregation framework that is private, fair, robust, and auditable. Kaires enables data consumers to build aggregation and linear regression models while maintaining the privacy of individual data providers as well as the confidentiality of the model parameters. To achieve these goals, Kaires employs a fault-tolerant multi-party computation protocol for computing aggregate statistics backed with a system for auditable management of private data. Besides enabling the data providers to have fine-grained access-control over their data, the system is also fault-tolerant with no single point of compromise or failure.

Aug 14, 2019
Santa Clara, CA, USA