STAR: Secret sharing for private threshold aggregation reporting
File(s)
Accepted version
Author(s)
Type
Conference Paper
Abstract
Threshold aggregation reporting systems promise a practical, privacy-preserving solution for developers to learn how their applications are used in-the-wild. Unfortunately, proposed systems to date prove impractical for wide scale adoption, suffering from a combination of requiring: i) prohibitive trust assumptions; ii) high computation costs; or iii) massive user bases. As a result, adoption of truly-private approaches has been limited to only a small number of enormous (and enormously costly) projects.
In this work, we improve the state of private data collection by proposing STAR, a highly efficient, easily deployable system for providing cryptographically-enforced κ-anonymity protections on user data collection. The STAR protocol is easy to implement and cheap to run, all while providing privacy properties similar to, or exceeding the current state-of-the-art. Measurements of our open-source implementation of STAR find that it is 1773x quicker, requires 62.4x less communication, and is 24x cheaper to run than the existing state-of-the-art.
In this work, we improve the state of private data collection by proposing STAR, a highly efficient, easily deployable system for providing cryptographically-enforced κ-anonymity protections on user data collection. The STAR protocol is easy to implement and cheap to run, all while providing privacy properties similar to, or exceeding the current state-of-the-art. Measurements of our open-source implementation of STAR find that it is 1773x quicker, requires 62.4x less communication, and is 24x cheaper to run than the existing state-of-the-art.
Date Issued
2022-11-07
Date Acceptance
2022-11-01
Citation
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022, pp.697-710
Publisher
ACM
Start Page
697
End Page
710
Journal / Book Title
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security
Copyright Statement
© 2022 Association for Computing Machinery.
Identifier
http://dx.doi.org/10.1145/3548606.3560631
Source
CCS '22: 2022 ACM SIGSAC Conference on Computer and Communications Security
Publication Status
Published
Start Date
2022-11-07
Finish Date
2022-11-11
Coverage Spatial
Los Angeles, CA, USA
Date Publish Online
2022-11-07