Scalable Multiparty Garbling
Author(s)
Beck, Gabrielle; Goel, Aarushi; Hegde, Aditya; Jain, Abhishek; Jin, Zhengzhong; Kaptchuk, Gabriel; ... Show more Show less
Download3576915.3623132.pdf (1.161Mb)
Publisher with Creative Commons License
Publisher with Creative Commons License
Creative Commons Attribution
Terms of use
Metadata
Show full item recordAbstract
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.
Date issued
2023-11-15Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence LaboratoryPublisher
ACM|Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security
Citation
Beck, Gabrielle, Goel, Aarushi, Hegde, Aditya, Jain, Abhishek, Jin, Zhengzhong et al. 2023. "Scalable Multiparty Garbling."
Version: Final published version
ISBN
979-8-4007-0050-7
Collections
The following license files are associated with this item: