Secret sharing from correlated Gaussian random variables and public communication

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Rana, Vidhi
Chou, Rémi
Kwon, Hyuck M.

Rana, V., Chou, R. A., & Kwon, H. (2021). Secret sharing from correlated Gaussian random variables and public communication. Paper presented at the 2020 IEEE Information Theory Workshop, ITW 2020, doi:10.1109/ITW46852.2021.9457636


We study a secret sharing problem, where a dealer distributes shares of a secret among a set of participants under the constraints that (i) authorized sets of users can recover the secret by pooling their shares, (ii) non-authorized sets of colluding users cannot learn any information about the secret. We assume that the dealer and the participants observe the realizations of correlated Gaussian random variables and that the dealer can communicate with the participants through a one-way, authenticated, rate-limited, and public channel. Our main result is a closed-form characterization of the trade-off between secret rate and public communication rate. Unlike traditional secret sharing protocols, in our setting, no perfectly secure channel is needed between the dealer and the participants, and the size of the shares does not depend exponentially but rather linearly on the number of participants and the size of the secret for arbitrary access structures.

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