Uncertain inference control in privacy protection

Authors:
Xiangdong An;Dawn Jutla;Nick Cercone;Charnyote Pluempitiwiriyawej;Hai Wang
Affiliations:
York University, Department of Computer Science and Engineering, M3J 1P3, Toronto, ON, Canada;Saint Mary’s University, Department of Finance, Information Systems, and Management Science, B3H 3C3, Halifax, NS, Canada;York University, Department of Computer Science and Engineering, M3J 1P3, Toronto, ON, Canada;Mahidol University, Faculty of Information and Communication Technology, Salaya, 73170, Nakhon Pathom, Thailand;Saint Mary’s University, Department of Finance, Information Systems, and Management Science, B3H 3C3, Halifax, NS, Canada
Venue:
International Journal of Information Security
Year:
2009

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Adaptive information-sharing for privacy-aware mobile social networks

Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing

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Abstract

Context management is the key enabler for emerging context-aware applications, and it includes context acquisition, understanding and exchanging. Context exchanging should be made privacy-conscious. We can specify privacy preferences to limit the disclosure of sensitive contexts, but the sensitive contexts could still be derived from those insensitive. To date, there have been very few inference control mechanisms for context management, especially when the environments are uncertain. In this paper, we present an inference control method for private context protection in uncertain environments.