Paper 2023/1534 Original: eprint.iacr.org/2023/1534 ↗

Evolving Secret Sharing Made Short

Danilo Francati
Daniele Venturi
Abstract

Evolving secret sharing (Komargodski, Naor, and Yogev, TCC’16) generalizes the notion of secret sharing to the setting of evolving access structures, in which the share holders are added to the system in an online manner, and where the dealer does not know neither the access structure nor the maximum number of parties in advance. Here, the main difficulty is to distribute shares to the new players without updating the shares of old players; moreover, one would like to minimize the share size as a function of the number of players. In this paper, we initiate a systematic study of evolving secret sharing in the computational setting, where the maximum number of parties is polynomial in the security parameter, but the dealer still does not know this value, neither it knows the access structure in advance. Moreover, the privacy guarantee only holds against computationally bounded adversaries corrupting an unauthorized subset of the players. Our main result is that for many interesting, and practically relevant, evolving access structures (including graphs access structures, DNF and CNF formulas access structures, monotone circuits access structures, and threshold access structures), under standard hardness assumptions, there exist efficient secret sharing schemes with computational privacy and in which the shares are succinct (i.e., much smaller compared to the size of a natural computational representation of the evolving access structure).

Metadata
Available format(s)
PDF
Category
Cryptographic protocols
Publication info
Preprint.
History
2024-09-13: last updated
2023-10-07: published
Short URL
https://ia.cr/2023/1534
License
https://creativecommons.org/licenses/by/4.0/

BibTeX

@misc{cryptoeprint:2023/1534,
      author = {Danilo Francati and Daniele Venturi},
      title = {Evolving Secret Sharing Made Short},
      howpublished = {Cryptology {ePrint} Archive, Paper 2023/1534},
      year = {2023},
      url = {https://eprint.iacr.org/2023/1534}
}
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