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View all- Zarei AVinterbo S(2024)Statistically Secure Multiparty Computation of a Biased CoinSecurity and Trust Management10.1007/978-3-031-76371-7_5(66-81)Online publication date: 19-Sep-2024
Secure Multiparty Sampling of a Biased Coin for Differential Privacy
Pages 310 - 320
Abstract
Sampling a biased coin is a key primitive in designing secure multiparty computation (MPC) for differentially private mechanisms. We explore privately sampling a biased coin from l unbiased coins and offer an unconditionally secure MPC protocol for this task that can be implemented using either (when l is even) or (when l is odd) multiplications in 7 rounds. This protocol assumes control over the choice of the underlying field size and is compatible with any linear secret sharing scheme with a multiplication protocol. The protocol is also secure against active adversaries when the underlying secret sharing scheme is secure. Eriguchi and colleagues proposed a protocol to generate noise for differential privacy, incorporating a sub-protocol for biased coins. Replacing their sub-protocol with ours significantly reduces communication needs as the number of multiplications needed per biased coin becomes roughly 3/8 of the original.
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Published In
Sep 2023
517 pages
ISBN:978-3-031-54203-9
DOI:10.1007/978-3-031-54204-6
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
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Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 01 March 2024
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View all- Zarei AVinterbo S(2024)Statistically Secure Multiparty Computation of a Biased CoinSecurity and Trust Management10.1007/978-3-031-76371-7_5(66-81)Online publication date: 19-Sep-2024