The Library
Aggregation and transformation of vector-valued messages in the shuffle model of differential privacy
Tools
Tools
Tools
Scott, Mary, Cormode, Graham and Maple, Carsten (2022) Aggregation and transformation of vector-valued messages in the shuffle model of differential privacy. IEEE Transactions on Information Forensics and Security, 17 . pp. 612-627. doi:10.1109/TIFS.2022.3147643
|
PDF
WRAP-aggregation-transformation-vector-valued-messages-shuffle-model-differential-privacy-2021.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (5Mb) | Preview |
Official URL: http://dx.doi.org/10.1109/TIFS.2022.3147643
Abstract
Advances in communications, storage and computational technology allow significant quantities of data to be collected and processed by distributed devices. Combining the information from these endpoints can realize significant societal benefit but presents challenges in protecting the privacy of individuals, especially important in an increasingly regulated world. Differential privacy (DP) is a technique that provides a rigorous and provable privacy guarantee for aggregation and release. The Shuffle Model for DP has been introduced to overcome challenges regarding the accuracy of local-DP algorithms and the privacy risks of central-DP. In this work we introduce a new protocol for vector aggregation in the context of the Shuffle Model. The aim of this paper is twofold; first, we provide a single message protocol for the summation of real vectors in the Shuffle Model, using advanced composition results. Secondly, we provide an improvement on the bound on the error achieved through using this protocol through the implementation of a Discrete Fourier Transform, thereby minimizing the initial error at the expense of the loss in accuracy through the transformation itself. This work will further the exploration of more sophisticated structures such as matrices and higher-dimensional tensors in this context, both of which are reliant on the functionality of the vector case.
| Item Type: | Journal Article | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||||||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) |
||||||||||||
| Library of Congress Subject Headings (LCSH): | Computer security, Computer networks -- Security measures, Artificial intelligence, Data mining, Computer programming, Data encryption (Computer science) | ||||||||||||
| Journal or Publication Title: | IEEE Transactions on Information Forensics and Security | ||||||||||||
| Publisher: | IEEE | ||||||||||||
| ISSN: | 1556-6013 | ||||||||||||
| Official Date: | 28 January 2022 | ||||||||||||
| Dates: |
|
||||||||||||
| Volume: | 17 | ||||||||||||
| Page Range: | pp. 612-627 | ||||||||||||
| DOI: | 10.1109/TIFS.2022.3147643 | ||||||||||||
| Status: | Peer Reviewed | ||||||||||||
| Publication Status: | Published | ||||||||||||
| Access rights to Published version: | Open Access | ||||||||||||
| RIOXX Funder/Project Grant: |
|
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
Downloads
Downloads per month over past year
