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Using Secure Multi-Party Computation to Protect Privacy on a Permissioned Blockchain

The development of information technology has brought great convenience to our lives, but at the same time, the unfairness and privacy issues brought about by traditional centralized systems cannot be ignored. Blockchain is a peer-to-peer and decentralized ledger technology that has the characterist...

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Detalles Bibliográficos
Autores principales: Zhou, Jiapeng, Feng, Yuxiang, Wang, Zhenyu, Guo, Danyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7927103/
https://www.ncbi.nlm.nih.gov/pubmed/33672175
http://dx.doi.org/10.3390/s21041540
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author Zhou, Jiapeng
Feng, Yuxiang
Wang, Zhenyu
Guo, Danyi
author_facet Zhou, Jiapeng
Feng, Yuxiang
Wang, Zhenyu
Guo, Danyi
author_sort Zhou, Jiapeng
collection PubMed
description The development of information technology has brought great convenience to our lives, but at the same time, the unfairness and privacy issues brought about by traditional centralized systems cannot be ignored. Blockchain is a peer-to-peer and decentralized ledger technology that has the characteristics of transparency, consistency, traceability and fairness, but it reveals private information in some scenarios. Secure multi-party computation (MPC) guarantees enhanced privacy and correctness, so many researchers have been trying to combine secure MPC with blockchain to deal with privacy and trust issues. In this paper, we used homomorphic encryption, secret sharing and zero-knowledge proofs to construct a publicly verifiable secure MPC protocol consisting of two parts—an on-chain computation phase and an off-chain preprocessing phase—and we integrated the protocol as part of the chaincode in Hyperledger Fabric to protect the privacy of transaction data. Experiments showed that our solution performed well on a permissioned blockchain. Most of the time taken to complete the protocol was spent on communication, so the performance has a great deal of room to grow.
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spelling pubmed-79271032021-03-04 Using Secure Multi-Party Computation to Protect Privacy on a Permissioned Blockchain Zhou, Jiapeng Feng, Yuxiang Wang, Zhenyu Guo, Danyi Sensors (Basel) Article The development of information technology has brought great convenience to our lives, but at the same time, the unfairness and privacy issues brought about by traditional centralized systems cannot be ignored. Blockchain is a peer-to-peer and decentralized ledger technology that has the characteristics of transparency, consistency, traceability and fairness, but it reveals private information in some scenarios. Secure multi-party computation (MPC) guarantees enhanced privacy and correctness, so many researchers have been trying to combine secure MPC with blockchain to deal with privacy and trust issues. In this paper, we used homomorphic encryption, secret sharing and zero-knowledge proofs to construct a publicly verifiable secure MPC protocol consisting of two parts—an on-chain computation phase and an off-chain preprocessing phase—and we integrated the protocol as part of the chaincode in Hyperledger Fabric to protect the privacy of transaction data. Experiments showed that our solution performed well on a permissioned blockchain. Most of the time taken to complete the protocol was spent on communication, so the performance has a great deal of room to grow. MDPI 2021-02-23 /pmc/articles/PMC7927103/ /pubmed/33672175 http://dx.doi.org/10.3390/s21041540 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhou, Jiapeng
Feng, Yuxiang
Wang, Zhenyu
Guo, Danyi
Using Secure Multi-Party Computation to Protect Privacy on a Permissioned Blockchain
title Using Secure Multi-Party Computation to Protect Privacy on a Permissioned Blockchain
title_full Using Secure Multi-Party Computation to Protect Privacy on a Permissioned Blockchain
title_fullStr Using Secure Multi-Party Computation to Protect Privacy on a Permissioned Blockchain
title_full_unstemmed Using Secure Multi-Party Computation to Protect Privacy on a Permissioned Blockchain
title_short Using Secure Multi-Party Computation to Protect Privacy on a Permissioned Blockchain
title_sort using secure multi-party computation to protect privacy on a permissioned blockchain
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7927103/
https://www.ncbi.nlm.nih.gov/pubmed/33672175
http://dx.doi.org/10.3390/s21041540
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