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Personalized privacy in open data sharing scenarios

David Sánchez (Department of Computer Engineering and Mathematics, Universitat Rovira i Virgili, Tarragona, Spain)
Alexandre Viejo (Department of Computer Engineering and Mathematics, Universitat Rovira i Virgili, Tarragona, Spain)

Online Information Review

ISSN: 1468-4527

Article publication date: 12 June 2017

Abstract

Purpose

The purpose of this paper is to propose a privacy-preserving paradigm for open data sharing based on the following foundations: subjects have unique privacy requirements; personal data are usually published incrementally in different sources; and privacy has a time-dependent element.

Design/methodology/approach

This study first discusses the privacy threats related to open data sharing. Next, these threats are tackled by proposing a new privacy-preserving paradigm. The main challenges related to the enforcement of the paradigm are discussed, and some suitable solutions are identified.

Findings

Classic privacy-preserving mechanisms are ineffective against observers constantly monitoring and aggregating pieces of personal data released through the internet. Moreover, these methods do not consider individual privacy needs.

Research limitations/implications

This study characterizes the challenges to the tackled by a new paradigm and identifies some promising works, but further research proposing specific technical solutions is suggested.

Practical implications

This work provides a natural solution to dynamic and heterogeneous open data sharing scenarios that require user-controlled personalized privacy protection.

Social implications

There is an increasing social understanding of the privacy threats that the uncontrolled collection and exploitation of personal data may produce. The new paradigm allows subjects to be aware of the risks inherent to their data and to control their release.

Originality/value

Contrary to classic data protection mechanisms, the new proposal centers privacy protection on the individuals, and considers the privacy risks through the whole life cycle of the data release.

Keywords

Acknowledgements

This work was partly supported by the European Commission (projects H2020-644024 “CLARUS” and H2020-700540 “CANVAS”), by the Spanish Government (projects TIN2014-57364-C2-R “SmartGlacis” and TIN2016-80250-R “Sec-MCloud”) and by the Government of Catalonia under Grant No. 2014 SGR 537. The opinions expressed in this paper are those of the authors and do not necessarily reflect the views of UNESCO.

Citation

Sánchez, D. and Viejo, A. (2017), "Personalized privacy in open data sharing scenarios", Online Information Review, Vol. 41 No. 3, pp. 298-310. https://doi.org/10.1108/OIR-01-2016-0011

Publisher

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Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited