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)
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Status: |
Published |
Creators/Authors: |
|
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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