학술논문

Efficient Noise Generation Protocols for Differentially Private Multiparty Computation
Document Type
Periodical
Source
IEEE Transactions on Dependable and Secure Computing IEEE Trans. Dependable and Secure Comput. Dependable and Secure Computing, IEEE Transactions on. 20(6):4486-4501 Jan, 2023
Subject
Computing and Processing
Protocols
Differential privacy
Complexity theory
Cryptography
Costs
Privacy
Noise generators
secure multiparty computation
secret sharing
Language
ISSN
1545-5971
1941-0018
2160-9209
Abstract
To bound information leakage in outputs of protocols, it is important to construct secure multiparty computation protocols which output differentially private values perturbed by the addition of noise. However, previous noise generation protocols have round and communication complexity growing with differential privacy budgets, or require parties to locally generate non-uniform noise, which makes it difficult to guarantee differential privacy against active adversaries. We propose three kinds of protocols for generating noise drawn from certain distributions providing differential privacy. The two of them generate noise from finite-range variants of the discrete Laplace distribution. For $(\epsilon,\delta )$(ε,δ)-differential privacy, they only need constant numbers of rounds independent of $\epsilon,\delta$ε,δ while the previous protocol needs the number of rounds depending on $\delta$δ. The two protocols are incomparable as they make a trade-off between round and communication complexity. Our third protocol non-interactively generate shares of noise from the binomial distribution by predistributing keys for a pseudorandom function. It achieves communication complexity independent of $\epsilon$ε or $\delta$δ for the computational analogue of $(\epsilon,\delta )$(ε,δ)-differential privacy while the previous protocols require communication complexity depending on $\epsilon$ε. We also prove that our protocols can be extended so that they provide differential privacy in the active setting.