On Choosing Between Privacy Preservation Mechanisms for Mobile Trajectory Data Sharing

Rajkarn Singh, George Theodorakopoulos, Mahesh K. Marina, Myrto Arapinis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Various notions of privacy preservation have been proposed for mobile trajectory data sharing/publication. The privacy guarantees provided by these approaches are theoretically very different and cannot be directly compared against each other. They are motivated by different adversary models, making varying assumptions about adversary’s background knowledge and intention. A clear comparison between existing mechanisms is missing, making it difficult when a data aggregator/owner needs to pick a mechanism for a given application scenario. We seek to fill this gap by proposing a measure called STRAP that allows comparison of different trajectory privacy mechanisms on a common scale. We also study the trade-off between privacy and utility i.e., how different mechanisms perform when utility constraints are imposed over them. Using STRAP over two real mobile trajectory datasets, we compare state of the art mechanisms for trajectory data privacy and demonstrate the value of the proposed measure.
Original languageEnglish
Title of host publication2018 IEEE Conference on Communications and Network Security (CNS)
Place of PublicationBeijing, China
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages9
ISBN (Electronic)978-1-5386-4586-4
ISBN (Print)978-1-5386-4587-1
DOIs
Publication statusPublished - 13 Aug 2018
Event6th Annual IEEE Conference on Communications and Network Security - Beijing, China
Duration: 30 May 20181 Jun 2018
http://cns2018.ieee-cns.org/

Conference

Conference6th Annual IEEE Conference on Communications and Network Security
Abbreviated titleIEEE CNS 2018
CountryChina
CityBeijing
Period30/05/181/06/18
Internet address

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