research-article

Pointproofs: Aggregating Proofs for Multiple Vector Commitments

Authors:

Sergey Gorbunov,

Zhenfei ZhangAuthors Info & Claims

CCS '20: Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security

Pages 2007 - 2023

https://doi.org/10.1145/3372297.3417244

Published: 02 November 2020 Publication History

Abstract

Vector commitments enable a user to commit to a sequence of values and provably reveal one or many values at specific posi- tions at a later time. In this work, we construct Pointproofs? a new vector commitment scheme that supports non-interactive aggregation of proofs across multiple commitments. Our construction enables any third party to aggregate a collection of proofs with respect to different, independently computed commitments into a single proof represented by an elliptic curve point of 48-bytes. In addition, our scheme is hiding: a commitment and proofs for some values reveal no information about the remaining values. We build Pointproofs and demonstrate how to apply them to blockchain smart contracts. In our example application, Pointproofs reduce bandwidth overheads for propagating a block of transactions by at least 60% compared to prior state- of-art vector commitments. Pointproofs are also efficient: on a single-thread, it takes 0.08 seconds to generate a proof for 8 values with respect to one commitment, 0.25 seconds to aggregate 4000 such proofs across multiple commitments into one proof, and 23 seconds (0.7 ms per value proven) to verify the aggregated proof.

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Index Terms

Pointproofs: Aggregating Proofs for Multiple Vector Commitments
1. Security and privacy
  1. Cryptography
  2. Formal methods and theory of security

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cover image ACM Conferences

CCS '20: Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security

October 2020

2180 pages

ISBN:9781450370899

DOI:10.1145/3372297

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University of South Florida, USA
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University of South Florida, USA
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University of Maryland, USA
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University of California-Santa Barbara, USA

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Published: 02 November 2020

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Cited By

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https://doi.org/10.3390/app15020554
Yang HFeng DQin J(2025)Towards Efficient Verifiable Cloud Storage and Distribution for Large-Scale Data StreamingIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2025.352664236:3(487-501)Online publication date: Mar-2025
https://doi.org/10.1109/TPDS.2025.3526642
Yang YChen YLiu ZTan CLuo Y(2025)Verifiable and Redactable Blockchain for Internet of Vehicles Data SharingIEEE Internet of Things Journal10.1109/JIOT.2024.348380912:4(4249-4261)Online publication date: 15-Feb-2025
https://doi.org/10.1109/JIOT.2024.3483809
Miao MZhao SLi JWei JSusilo W(2025)Practically secure linear-map vector commitment and its applicationsComputer Standards & Interfaces10.1016/j.csi.2024.10388591(103885)Online publication date: Jan-2025
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