Publication Type

Conference Proceeding Article

Version

Publisher’s Version

Publication Date

1-2016

Abstract

There are several recent research studies on privacy-preserving aggregation of time series data, where an aggregator computes an aggregation of multiple users' data without learning each individual's private input value. However, none of the existing schemes allows the aggregation result to be verified for integrity. In this paper, we present a new data aggregation scheme that protects user privacy as well as integrity of the aggregation. Towards this end, we first propose an aggregate signature scheme in a multi-user setting without using bilinear maps. We then extend the aggregate signature scheme into a solution for privacy-preserving and verifiable data aggregation. The solution allows multiple users to periodically send encrypted data to an untrusted aggregator such that the latter is able to compute the sum of the input data values and verify its integrity, without learning any other information. A formal security analysis shows that the solution is semantically secure and unforgeable.

Keywords

Aggregate signature, Data aggregation, Data privacy, Verifiable computation

Discipline

Databases and Information Systems | Information Security

Research Areas

Cybersecurity; Data Management and Analytics

Publication

Proceedings of the Singapore Cyber-Security Conference (SG-CRC) 2016: Singapore, 2016, January 14-15

Volume

14

First Page

115

Last Page

122

ISBN

9781614996170

Identifier

10.3233/978-1-61499-617-0-115

Publisher

IOS Press

City or Country

Amsterdam

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org./10.3233/978-1-61499-617-0-115

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