Paper 2014/256
Private and Dynamic Time-Series Data Aggregation with Trust Relaxation
Iraklis Leontiadis, Kaoutar Elkhiyaoui, and Refik Molva
Abstract
Abstract. With the advent of networking applications collecting user data on a massive scale, the privacy of individual users appears to be a major concern. The main challenge is the design of a solution that allows the data analyzer to compute global statistics over the set of individual inputs that are protected by some confidentiality mechanism. Joye et al. [7] recently suggested a solution that allows a centralized party to compute the sum of encrypted inputs collected through a smart metering network. The main shortcomings of this solution are its reliance on a trusted dealer for key distribution and the need for frequent key updates. In this paper we introduce a secure protocol for aggregation of time series data that is based on the Joye et al. [7] scheme and in which the main shortcomings of the latter, namely, the requirement for key updates and for the trusted dealer are eliminated. Moreover our scheme supports a dynamic group management, whereby as opposed to Joye et al. [7] leave and join operations do not trigger a key update at the users.
Metadata
- Available format(s)
-
PDF
- Publication info
- Published elsewhere. Minor revision. CANS 2014
- DOI
- 10.1007/978-3-319-12280-9_20
- Keywords
- data aggregationprivacytime-series data
- Contact author(s)
- leontiad @ eurecom fr
- History
- 2015-02-20: last of 5 revisions
- 2014-04-20: received
- See all versions
- Short URL
- https://ia.cr/2014/256
- License
-
CC BY
BibTeX
@misc{cryptoeprint:2014/256,
author = {Iraklis Leontiadis and Kaoutar Elkhiyaoui and Refik Molva},
title = {Private and Dynamic Time-Series Data Aggregation with Trust Relaxation},
howpublished = {Cryptology {ePrint} Archive, Paper 2014/256},
year = {2014},
doi = {10.1007/978-3-319-12280-9_20},
url = {https://eprint.iacr.org/2014/256}
}
