A Decentralized Information Marketplace Preserving Input and Output Privacy
Authors: 
Steven Golob, Sikha Pentyala, Rafael Dowsley, Bernardo David, Mario Larangeira, Martine De Cock, and Anderson NascimentoAuthors Info & Claims
Steven Golob, Sikha Pentyala, Rafael Dowsley, Bernardo David, Mario Larangeira, Martine De Cock, and Anderson NascimentoAuthors Info & ClaimsJune 2023
Pages 1 - 6
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.
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Published In
June 2023
57 pages
ISBN:9798400708466
DOI:10.1145/3600046
Copyright © 2023 Owner/Author.
This work is licensed under a Creative Commons Attribution International 4.0 License.
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Association for Computing Machinery
New York, NY, United States
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Published: 07 September 2023
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