Towards location privacy awareness on geo-social networks

Alrayes, Fatma and Abdelmoty, Alia ORCID: https://orcid.org/0000-0003-2031-4413 2016. Towards location privacy awareness on geo-social networks. Presented at: 2016 10th International Conference on Next Generation Mobile Applications, Security and Technologies (NGMAST), Cardiff, UK, 24-26 August 2016. Next Generation Mobile Applications, Security and Technologies (NGMAST), 2016 10th International Conference on. IEEE, p. 105. 10.1109/NGMAST.2016.26

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Abstract

With the current trend of embedding location services within social networks, an ever growing amount of users' spatiotemporal tracks are being collected and used to generate user profiles. Issues of personal privacy and especially those stemming from tracking user location become more important to address. In this work, it is argued that support of location privacy awareness within social networks is needed to maintain the users' trust in their services. Current practices of pre-configuring location disclosure settings have been shown to be limited, where users' sense of location privacy dynamically change with context. In this paper, location privacy awareness is considered within a composite view of place, time and social data recorded in user profiles. The paper examines the possible threats to personal privacy from exposure of this data and the design of feedback tools to allow users to control their privacy. A user study is used to examine the impact of the feedback provided on users' perception of privacy and the link between their privacy concerns and their attitude towards using the geo-social network. Findings confirm the strong need for more transparent access to and control over user location profiles, and guide the proposal of recommendations to the design of more privacy-sensitive geo-social networks.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Publisher:	IEEE
ISBN:	9781509009497
Date of First Compliant Deposit:	13 April 2017
Date of Acceptance:	27 June 2016
Last Modified:	21 Oct 2022 07:26
URI:	https://orca.cardiff.ac.uk/id/eprint/99870

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