New technique for chosen-ciphertext security based on non-interactive zero-knowledge

Minhye Seo, Michel Abdalla, Dong Hoon Lee, Jong Hwan Park*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    3 Citations (Scopus)

    Abstract

    In this study, we propose a new method for conversion from a one-way (OW)-secure key encapsulation mechanism (KEM) into a chosen-ciphertext (CCA) secure KEM in the random oracle model. Our conversion method is based on the non-interactive zero-knowledge (NIZK) proof system for proving the relationships (e.g., equality or linearity) of discrete logarithms, where the security analysis of our conversion method depends on the NIZK properties of soundness and zero-knowledge. Our conversion method achieves tight security reduction and it is semi-generic in the sense that other than OW-security, a KEM should be NIZK-compatible. From a theoretical viewpoint, our conversion method can be considered as the corresponding approach for obtaining an efficient signature by applying the Fiat–Shamir transform to the NIZK system. We applied our conversion method to several OW-secure (identity-based) KEMs and compared the results with those obtained by previous methods for achieving CCA security.

    Original languageEnglish
    Pages (from-to)18-35
    Number of pages18
    JournalInformation Sciences
    Volume490
    DOIs
    Publication statusPublished - 2019 Jul

    Bibliographical note

    Funding Information:
    This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No. 2016-6-00600, A Study on Functional Encryption: Construction, Security Analysis, and Implementation).

    Publisher Copyright:
    © 2019

    Keywords

    • Chosen-ciphertext security
    • NIZK
    • Random oracle model

    ASJC Scopus subject areas

    • Software
    • Control and Systems Engineering
    • Theoretical Computer Science
    • Computer Science Applications
    • Information Systems and Management
    • Artificial Intelligence

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