Probabilistic Secret Sharing

Authors Paolo D'Arco , Roberto De Prisco , Alfredo De Santis , Angel Pérez del Pozo , Ugo Vaccaro

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Author Details

Paolo D'Arco
  • Dipartimento di Informatica, Università of Salerno, Italy
Roberto De Prisco
  • Dipartimento di Informatica, Università of Salerno, Italy
Alfredo De Santis
  • Dipartimento di Informatica, Università of Salerno, Italy
Angel Pérez del Pozo
  • Departamento de Matemática Aplicada, Ciencia e Ingeniería de los Materiales y Tecnología Electrónica, Universidad Rey Juan Carlos, Madrid, Spain
Ugo Vaccaro
  • Dipartimento di Informatica, Università of Salerno, Italy

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Paolo D'Arco, Roberto De Prisco, Alfredo De Santis, Angel Pérez del Pozo, and Ugo Vaccaro. Probabilistic Secret Sharing. In 43rd International Symposium on Mathematical Foundations of Computer Science (MFCS 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 117, pp. 64:1-64:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


In classical secret sharing schemes a dealer shares a secret among a set of participants in such a way that qualified subsets can reconstruct the secret, while forbidden ones do not get any kind of information about it. The basic parameter to optimize is the size of the shares, that is, the amount of secret information that the dealer has to give to participants. In this paper we formalize a notion of probabilistic secret sharing schemes, in which qualified subsets can reconstruct the secret but only with a certain controlled probability. We show that, by allowing a bounded error in the reconstruction of the secret, it is possible to drastically reduce the size of the shares the participants get (with respect to classical secret sharing schemes). We provide efficient constructions both for threshold access structures on a finite set of participants and for evolving threshold access structures, where the set of participants is potentially infinite. Some of our constructions yield shares of constant size (i.e., not depending on the number of participants) and an error probability of successfully reconstructing the secret which can be made as close to 1 as desired.

Subject Classification

ACM Subject Classification
  • Security and privacy → Mathematical foundations of cryptography
  • Secret sharing
  • probabilistic secret sharing
  • evolving secret sharing


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