Consensual and Privacy-Preserving Sharing of Multi-Subject and Interdependent Data

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State: Public
Version: author
Serval ID
serval:BIB_0D8D70E207E3
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Institution
Title
Consensual and Privacy-Preserving Sharing of Multi-Subject and Interdependent Data
Title of the conference
Proceedings of the 25th Network and Distributed System Security Symposium (NDSS)
Author(s)
Olteanu A.M., Huguenin K., Dacosta I., Hubaux J.-P.
Publisher
Internet Society
Address
San Diego, CA, USA
Publication state
Published
Issued date
02/2018
Peer-reviewed
Oui
Pages
1-16
Language
english
Abstract
Individuals share increasing amounts of personal data online. This data often involves–or at least has privacy implications for–data subjects other than the individuals who shares it (e.g., photos, genomic data) and the data is shared without their consent. A sadly popular example, with dramatic consequences, is revenge pornography. In this paper, we propose ConsenShare, a system for sharing, in a consensual (wrt the data subjects) and privacy-preserving (wrt both service providers and other individuals) way, data involving subjects other than the uploader. We describe a complete design and implementation of ConsenShare for photos, which relies on image processing and cryptographic techniques, as well as on a two-tier architecture (one entity for detecting the data subjects and contacting them; one entity for hosting the data and for collecting consent). We benchmark the performance (CPU and bandwidth) of ConsenShare by using a dataset of 20k photos from Flickr. We also conduct a survey targeted at Facebook users (N = 321). Our results are quite encouraging: The experimental results demonstrate the feasibility of our approach (i.e., acceptable overheads) and the survey results demonstrate a potential interest from the users.
Open Access
Yes
Create date
29/11/2017 10:40
Last modification date
21/08/2019 6:08
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