Automatic sanitization of social network data to prevent inference attacks

Authors:
Raymond D. Heatherly;Murat Kantarcioglu
Affiliations:
The University of Texas at Dallas, Richardson, TX, USA;The University of Texas at Dallas, Richardson, TX, USA
Venue:
Proceedings of the 20th international conference companion on World wide web
Year:
2011

Citing 2
Cited 0

To join or not to join: the illusion of privacy in social networks with mixed public and private user profiles

Proceedings of the 18th international conference on World wide web
Inferring private information using social network data

Proceedings of the 18th international conference on World wide web

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Abstract

As the privacy concerns related to information release in social networks become a more mainstream concern, data owners will need to utilize a variety of privacy-preserving methods of examining this data. Here, we propose a method of data generalization that applies to social networks and present some initial findings for the utility/privacy tradeoff required for its use.