Aardvark: An Asynchronous Authenticated Dictionary with Applications to Account-based Cryptocurrencies

Derek Leung, Yossi Gilad, Sergey Gorbunov, Leonid Reyzin, Nickolai Zeldovich

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

We design Aardvark, a novel authenticated dictionary with short proofs of correctness for lookups and modifications. Our design reduces storage requirements for transaction validation in cryptocurrencies by outsourcing data from validators to untrusted servers, which supply proofs of correctness of this data as needed. In this setting, short proofs are particularly important because proofs are distributed to many validators, and the transmission of long proofs can easily dominate costs. A proof for a piece of data in an authenticated dictionary may change whenever any (even unrelated) data changes. This presents a problem for concurrent issuance of cryptocurrency transactions, as proofs become stale. To solve this problem, Aardvark employs a versioning mechanism to safely accept stale proofs for a limited time. On a dictionary with 100 million keys, operation proof sizes are about 1KB in a Merkle Tree versus 100-200B in Aardvark. Our evaluation shows that a 32-core validator processes 1492-2941 operations per second, saving about 800× in storage costs relative to maintaining the entire state.

Original languageAmerican English
Title of host publicationProceedings of the 31st USENIX Security Symposium, Security 2022
PublisherUSENIX Association
Pages4237-4254
Number of pages18
ISBN (Electronic)9781939133311
StatePublished - 2022
Event31st USENIX Security Symposium, Security 2022 - Boston, United States
Duration: 10 Aug 202212 Aug 2022

Publication series

NameProceedings of the 31st USENIX Security Symposium, Security 2022

Conference

Conference31st USENIX Security Symposium, Security 2022
Country/TerritoryUnited States
CityBoston
Period10/08/2212/08/22

Bibliographical note

Funding Information:
The authors would like to thank Hoeteck Wee and Adam Suhl for their assistance with the analysis and implementation of vector commitments and Alin Tomescu for discussion on the paper's motivation and the security model. Yossi Gilad was supported by the Hebrew University cybersecurity research center, the Alon fellowship, and Mobileye. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. 1745302.

Funding Information:
The authors would like to thank Hoeteck Wee and Adam Suhl for their assistance with the analysis and implementation of vector commitments and Alin Tomescu for discussion on the paper’s motivation and the security model. Yossi Gilad was supported by the Hebrew University cybersecurity research center, the Alon fellowship, and Mobileye. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. 1745302.

Publisher Copyright:
© USENIX Security Symposium, Security 2022.All rights reserved.

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