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Anonymizing geo-social network datasets

Masoumzadeh, A and Joshi, J (2011) Anonymizing geo-social network datasets. In: UNSPECIFIED.

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Abstract

Geo-social networking systems, such as Foursquare and Face-book Places, where users perform interactions based on their self-reported locations are growing fast nowadays. The location-rich social network data collected in such systems could be of research interest for various purposes. However, such datasets are at the risk of user re-identification and consequently privacy violation of the involved users if they are not adequately anonymzied. In this paper, we study the problem of anonymizing a geo-social network dataset, based on adversarial knowledge on location information of its users. We introduce k-anonymity-based properties for guaranteeing anonymity based on location information, provide a realistic model of location data in geo-social networks, and propose corresponding anonymization algorithms. We also evaluate the proposed solutions using a synthetic GSN data-set. © 2011 ACM.


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Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Masoumzadeh, A
Joshi, Jjjoshi@pitt.eduJJOSHI0000-0003-4519-9802
Date: 1 December 2011
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: SPRINGL 2011 - Proceedings of the 4th ACM SIGSPATIAL International Workshop on Security and Privacy in GIS and LBS
Page Range: 25 - 32
Event Type: Conference
DOI or Unique Handle: 10.1145/2071880.2071886
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISBN: 9781450310321
Date Deposited: 10 Aug 2012 21:10
Last Modified: 01 May 2020 12:55
URI: http://d-scholarship.pitt.edu/id/eprint/13529

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