A decentralized information marketplace preserving input and output privacy

Steven Golob, Sikha Pentyala, Rafael Dowsley, Bernardo David, Mario Larangeira, Martine De Cock, Anderson Nascimento

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

Abstract

Data-driven applications are engines of economic growth and essential for progress in many domains. The data involved is often of a personal nature. We propose a decentralized information marketplace where data held by data providers, such as individual users can be made available for computation to data consumers, such as government agencies, research institutes, or companies who want to derive actionable insights or train machine learning models with the data while (1) protecting input privacy, (2) protecting output privacy, and (3) compensating data providers for making their sensitive information available for secure computation. We enable this privacy-preserving data exchange through a novel and carefully designed combination of a blockchain that supports smart contracts and two privacy-enhancing technologies: (1) secure multi-party computations, and (2) robust differential privacy guarantees.

Original languageEnglish
Title of host publicationDEC 2023 - Proceedings of the Second ACM Data Economy Workshop
EditorsGeorgia Koutrika, Nikolaos Laoutaris, Martino Trevisan
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages1-6
Number of pages6
ISBN (Electronic)9798400708466
DOIs
Publication statusPublished - 2023
EventACM Data Economy Workshop 2023 - Seattle, United States of America
Duration: 18 Jun 202318 Jun 2023
Conference number: 2nd
https://dl.acm.org/doi/proceedings/10.1145/3600046 (Proceedings)
https://sites.google.com/view/data-economy-2023/ (Website)

Conference

ConferenceACM Data Economy Workshop 2023
Abbreviated titleDEC 2023
Country/TerritoryUnited States of America
CitySeattle
Period18/06/2318/06/23
Internet address

Keywords

  • blockchain.
  • data consumer
  • data economy
  • Data holder
  • Differential Privacy
  • privacy budget
  • Secure Multiparty Computation

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