Randomness Recoverable Secret Sharing Schemes

Mohammad Hajiabadi, Shahram Khazaei, Behzad Vahdani

    Research output: Chapter in Book/Report/Conference proceedingConference contribution


    It is well-known that randomness is essential for secure cryptography. The randomness used in cryptographic primitives is not necessarily recoverable even by the party who can, e.g., decrypt or recover the underlying secret/message. Several cryptographic primitives that support randomness recovery have turned out useful in various applications. In this paper, we study randomness recoverable secret sharing schemes (RR-SSS), in both information-theoretic and computational settings and provide two results. First, we show that while every access structure admits a perfect RR-SSS, there are very simple access structures (e.g., in monotone AC0) that do not admit efficient perfect (or even statistical) RR-SSS. Second, we show that the existence of efficient computational RR-SSS for certain access structures in monotone AC0 implies the existence of one-way functions. This stands in sharp contrast to (non-RR) SSS schemes for which no such results are known. RR-SSS plays a key role in making advanced attributed-based encryption schemes randomness recoverable, which in turn have applications in the context of designated-verifier non-interactive zero knowledge.

    Original languageEnglish (US)
    Title of host publication4th Conference on Information-Theoretic Cryptography, ITC 2023
    EditorsKai-Min Chung
    PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
    ISBN (Electronic)9783959772716
    StatePublished - Jul 2023
    Event4th Conference on Information-Theoretic Cryptography, ITC 2023 - Aarhus, Denmark
    Duration: Jun 6 2023Jun 8 2023

    Publication series

    NameLeibniz International Proceedings in Informatics, LIPIcs
    ISSN (Print)1868-8969


    Conference4th Conference on Information-Theoretic Cryptography, ITC 2023

    All Science Journal Classification (ASJC) codes

    • Software

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