Delphi
Pratyush Mishra, Ryan Lehmkuhl, Akshayaram Srinivasan, Wenting Zheng, Raluca Ada Popa
Abstract
Many companies provide neural network prediction services to users for a wide range of applications. However, current prediction systems compromise one party's privacy: either the user has to send sensitive inputs to the service provider for classification, or the service provider must store its proprietary neural networks on the user's device. The former harms the personal privacy of the user, while the latter reveals the service provider's proprietary model.
Topics & Concepts
Service providerComputer scienceCompromiseService (business)Internet privacyComputer securityBusinessMarketingSocial scienceSociologyPrivacy-Preserving Technologies in DataMobile Crowdsensing and CrowdsourcingPrivacy, Security, and Data Protection