20 20

Transactions on
Data Privacy
Foundations and Technologies


Articles in Press

Accepted articles here

Latest Issues

Year 2018

Volume 11 Issue 3
Volume 11 Issue 2
Volume 11 Issue 1

Year 2017

Volume 10 Issue 3
Volume 10 Issue 2
Volume 10 Issue 1

Year 2016

Volume 9 Issue 3
Volume 9 Issue 2
Volume 9 Issue 1

Year 2015

Volume 8 Issue 3
Volume 8 Issue 2
Volume 8 Issue 1

Year 2014

Volume 7 Issue 3
Volume 7 Issue 2
Volume 7 Issue 1

Year 2013

Volume 6 Issue 3
Volume 6 Issue 2
Volume 6 Issue 1

Year 2012

Volume 5 Issue 3
Volume 5 Issue 2
Volume 5 Issue 1

Year 2011

Volume 4 Issue 3
Volume 4 Issue 2
Volume 4 Issue 1

Year 2010

Volume 3 Issue 3
Volume 3 Issue 2
Volume 3 Issue 1

Year 2009

Volume 2 Issue 3
Volume 2 Issue 2
Volume 2 Issue 1

Year 2008

Volume 1 Issue 3
Volume 1 Issue 2
Volume 1 Issue 1

Volume 11 Issue 2

PRUDEnce: a System for Assessing Privacy Risk vs Utility in Data Sharing Ecosystems

Francesca Pratesi(a),(b),(*), Anna Monreale(b), Roberto Trasarti(a), Fosca Giannotti(a), Dino Pedreschi(b), Tadashi Yanagihara(c)

Transactions on Data Privacy 11:2 (2018) 139 - 167

Abstract, PDF

(a) ISTI CNR, Pisa, Italy.

(b) University of Pisa, Pisa, Italy.

(c) KDDI Corporation of Tokyo, Japan.

e-mail:francesca.pratesi @isti.cnr.it; ; ; ; ;


Data describing human activities are an important source of knowledge useful for understanding individual and collective behavior and for developing a wide range of user services. Unfortunately, this kind of data is sensitive, because people's whereabouts may allow re-identification of individuals in a de-identified database. Therefore, Data Providers, before sharing those data, must apply any sort of anonymization to lower the privacy risks, but they must be aware and capable of controlling also the data quality, since these two factors are often a trade-off. In this paper we propose PRUDEnce (Privacy Risk versus Utility in Data sharing Ecosystems), a system enabling a privacy-aware ecosystem for sharing personal data. It is based on a methodology for assessing both the empirical (not theoretical) privacy risk associated to users represented in the data, and the data quality guaranteed only with users not at risk. Our proposal is able to support the Data Provider in the exploration of a repertoire of possible data transformations with the aim of selecting one specific transformation that yields an adequate trade-off between data quality and privacy risk. We study the practical effectiveness of our proposal over three data formats underlying many services, defined on real mobility data, i.e., presence data, trajectory data and road segment data.

* Corresponding author.

Follow us


ISSN: 1888-5063; ISSN (Digital): 2013-1631; D.L.:B-11873-2008; Web Site: http://www.tdp.cat/
Contact: Transactions on Data Privacy; Vicenç Torra; U. of Skövde; PO Box 408; 54128 Skövde; (Sweden); e-mail:tdp@tdp.cat
Note: TDP's web site does not use cookies. TDP does not keep information neither on IP addresses nor browsers. For the privacy policy access here.


Vicenç Torra, Last modified: 05 : 40 August 26 2018.