2022
DOI: 10.1007/s11128-022-03758-5
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Multiparty quantum private comparison based on quantum walks

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Cited by 3 publications
(1 citation statement)
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“…The research task of QMSC is to solve the problem of collaborative computing among multiple mutually distrusted players while ensuring the confidentiality of their privacy inputs. As the study develops in depth, researchers have further applied QSMC to establish secure schemes for various computing scenarios in distributed networks, such as anonymous voting [1,2], private comparison [3,4], and secure multiparty summation [5][6][7]. Within them, quantum secure multiparty summation (QSMS) is the most essential primitive in QSMC, which can be extended to other multiparty computations.…”
Section: Introductionmentioning
confidence: 99%
“…The research task of QMSC is to solve the problem of collaborative computing among multiple mutually distrusted players while ensuring the confidentiality of their privacy inputs. As the study develops in depth, researchers have further applied QSMC to establish secure schemes for various computing scenarios in distributed networks, such as anonymous voting [1,2], private comparison [3,4], and secure multiparty summation [5][6][7]. Within them, quantum secure multiparty summation (QSMS) is the most essential primitive in QSMC, which can be extended to other multiparty computations.…”
Section: Introductionmentioning
confidence: 99%