Paper 2023/099

Scalable Multiparty Garbling

Gabrielle Beck, Johns Hopkins University
Aarushi Goel, NTT Research
Aditya Hegde, Johns Hopkins University
Abhishek Jain, Johns Hopkins University
Zhengzhong Jin, Massachusetts Institute of Technology
Gabriel Kaptchuk, Boston University

Multiparty garbling is the most popular approach for constant-round secure multiparty computation (MPC). Despite being the focus of significant research effort, instantiating prior approaches to multiparty garbling results in constant-round MPC that can not realistically accommodate large numbers of parties. In this work we present the first global-scale multiparty garbling protocol. The per-party communication complexity of our protocol decreases as the number of parties participating in the protocol increases---for the first time matching the asymptotic communication complexity of non-constant round MPC protocols. Our protocol achieves malicious security in the honest-majority setting and relies on the hardness of the Learning Party with Noise assumption.

Available format(s)
Cryptographic protocols
Publication info
Multiparty ComputationGarblingLPN
Contact author(s)
becgabri @ cs jhu edu
aarushi goel @ ntt-research com
ahegde @ cs jhu edu
abhishek @ cs jhu edu
zzjin @ mit edu
kaptchuk @ bu edu
2023-01-27: approved
2023-01-26: received
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Creative Commons Attribution


      author = {Gabrielle Beck and Aarushi Goel and Aditya Hegde and Abhishek Jain and Zhengzhong Jin and Gabriel Kaptchuk},
      title = {Scalable Multiparty Garbling},
      howpublished = {Cryptology ePrint Archive, Paper 2023/099},
      year = {2023},
      note = {\url{}},
      url = {}
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