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Using Secure Multi-Party Computation to Protect Privacy on a Permissioned Blockchain
by
Feng, Yuxiang
, Zhou, Jiapeng
, Wang, Zhenyu
, Guo, Danyi
in
Access control
/ Blockchain
/ Cryptography
/ Data encryption
/ Digital currencies
/ Hyperledger Fabric
/ Peers
/ permissioned blockchain
/ Privacy
/ Protocol
/ secure multi-party computation
2021
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Using Secure Multi-Party Computation to Protect Privacy on a Permissioned Blockchain
by
Feng, Yuxiang
, Zhou, Jiapeng
, Wang, Zhenyu
, Guo, Danyi
in
Access control
/ Blockchain
/ Cryptography
/ Data encryption
/ Digital currencies
/ Hyperledger Fabric
/ Peers
/ permissioned blockchain
/ Privacy
/ Protocol
/ secure multi-party computation
2021
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Do you wish to request the book?
Using Secure Multi-Party Computation to Protect Privacy on a Permissioned Blockchain
by
Feng, Yuxiang
, Zhou, Jiapeng
, Wang, Zhenyu
, Guo, Danyi
in
Access control
/ Blockchain
/ Cryptography
/ Data encryption
/ Digital currencies
/ Hyperledger Fabric
/ Peers
/ permissioned blockchain
/ Privacy
/ Protocol
/ secure multi-party computation
2021
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Using Secure Multi-Party Computation to Protect Privacy on a Permissioned Blockchain
Journal Article
Using Secure Multi-Party Computation to Protect Privacy on a Permissioned Blockchain
2021
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Overview
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.
Publisher
MDPI AG,MDPI
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