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PSPAB: Privacy-preserving average procurement bidding system with double-spending checking

Several organizations use auctions in a procurement bidding system to maintain a low procurement cost. Although several privacy-preserving auction solutions for different application scenarios have been proposed over the past few decades, none of them can perform efficient average procurement biddin...

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Detalles Bibliográficos
Autores principales: Li, Li, Liu, Jiayong, Jia, Peng, Zheng, Rongfeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7595447/
https://www.ncbi.nlm.nih.gov/pubmed/33119611
http://dx.doi.org/10.1371/journal.pone.0240548
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author Li, Li
Liu, Jiayong
Jia, Peng
Zheng, Rongfeng
author_facet Li, Li
Liu, Jiayong
Jia, Peng
Zheng, Rongfeng
author_sort Li, Li
collection PubMed
description Several organizations use auctions in a procurement bidding system to maintain a low procurement cost. Although several privacy-preserving auction solutions for different application scenarios have been proposed over the past few decades, none of them can perform efficient average procurement bidding while ensuring strong privacy protection for the bids of suppliers. To address this problem, we propose PSPAB, a lightweight, secure average procurement bidding system based on cryptographic tools, to provide full privacy for bids. In addition, this system allows the procurement manager to identify the users in the case of double spending. We formally prove the security of PSPAB under a semi-honest adversary model. Experimental results validate the theoretical analysis and practical application of PSPAB in real-world scenarios.
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spelling pubmed-75954472020-11-03 PSPAB: Privacy-preserving average procurement bidding system with double-spending checking Li, Li Liu, Jiayong Jia, Peng Zheng, Rongfeng PLoS One Research Article Several organizations use auctions in a procurement bidding system to maintain a low procurement cost. Although several privacy-preserving auction solutions for different application scenarios have been proposed over the past few decades, none of them can perform efficient average procurement bidding while ensuring strong privacy protection for the bids of suppliers. To address this problem, we propose PSPAB, a lightweight, secure average procurement bidding system based on cryptographic tools, to provide full privacy for bids. In addition, this system allows the procurement manager to identify the users in the case of double spending. We formally prove the security of PSPAB under a semi-honest adversary model. Experimental results validate the theoretical analysis and practical application of PSPAB in real-world scenarios. Public Library of Science 2020-10-29 /pmc/articles/PMC7595447/ /pubmed/33119611 http://dx.doi.org/10.1371/journal.pone.0240548 Text en © 2020 Li et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Li, Li
Liu, Jiayong
Jia, Peng
Zheng, Rongfeng
PSPAB: Privacy-preserving average procurement bidding system with double-spending checking
title PSPAB: Privacy-preserving average procurement bidding system with double-spending checking
title_full PSPAB: Privacy-preserving average procurement bidding system with double-spending checking
title_fullStr PSPAB: Privacy-preserving average procurement bidding system with double-spending checking
title_full_unstemmed PSPAB: Privacy-preserving average procurement bidding system with double-spending checking
title_short PSPAB: Privacy-preserving average procurement bidding system with double-spending checking
title_sort pspab: privacy-preserving average procurement bidding system with double-spending checking
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7595447/
https://www.ncbi.nlm.nih.gov/pubmed/33119611
http://dx.doi.org/10.1371/journal.pone.0240548
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