Privacy protection among three antithetic-parties for context-aware services
Department
Software Engineering and Game Development
Document Type
Article
Publication Date
10-1-2021
Abstract
The popularity of context-aware services is improving the quality of life, while raising serious privacy issues. In order for users to receive quality service, they are at risk of leaking private information by adversaries that are possibly eavesdropping on the data and/or by the untrusted service platform selling off its data to adversaries. Game theory has been utilized as a powerful tool to achieve privacy preservation by strategically balancing the trade-off between profit (service) and cost (data leakage) for the user. However, most of the existing schemes cannot fully exploit the power of game theory, as they fail to depict the mutual relationship between any two (of the three) parties involved: user, platform, and adversary. Existing schemes are also not always able to provide specific guidance for a user to reduce the impact of the joint threats from the platform and adversary. In this paper, we design a privacy-preserving game to quantify the three parties’ concerns and capture interactions between any two of them. We also identify the best strategy for each party at a fine-grained level, i.e. specific settings, not simply binary choices. We validate the performance of our proposed game model through both a theoretical analysis and experiments.
Journal Title
Journal of Network and Computer Applications
Journal ISSN
10848045
Volume
191
Digital Object Identifier (DOI)
10.1016/j.jnca.2021.103115