ZKP6.2 Discrete-log-based Polynomial Commitments (KZG10)

ZKP学习笔记

ZK-Learning MOOC课程笔记

Lecture 6: Discrete-log-based Polynomial Commitments (Yupeng Zhang)

6.2 KZG polynomial commitment and its variants

  • KZG: [Kate-Zaverucha-Goldberg '2010]
  • Procedure
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  • Soundness: q-Strong Bilinear Diffie-Hellman (q-SBDH) assumption
    在这里插入图片描述

    • Formal Security Proof
      ZKP6.2 Discrete-log-based Polynomial Commitments (KZG10)_第5张图片

      • The key idea: decompose the fack value v ∗ v* v into a correct value f ( u ) f(u) f(u) and a difference δ \delta δ
  • Knowledge soundness and KoE assumption
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    • KZG with knowledge soundness: the commitment size is doubled
    • Solution: Generic group model (GGM) [Shoup’97, Maurer’05]
      • GGM can replace the KoE assumption and reduce the commitment size in KZG.
  • Properties of the KZG poly-commit
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  • Ceremony: A distributed generation of gp s.t. No one can reconstruct the trapdoor if at least one of the participants is honest and discards their secrets
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  • Variants of KZG polynomial commitment

    • Multivariate poly-commit [Papamanthou-Shi-Tamassia’13]
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    • Achieving zero-knowledge [ZGKPP’2018]
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    • Batch opening

      • single polynomial
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      • multiple polynomials
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  • Application

    • Plonk [Gabizon-Williamson-Ciobotaru’20]
      • Univariate KZG + Plonk Polynomial IOP
    • vSQL[ZGKPP’17], Libra[XZZPS’19]
      • Multivariate KZG + Sumcheck protocol / GKR protocol

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