Abstract
In the era of context-aware services, users are enjoying remarkable services based on data collected from a multitude of users. However, in order to benefit from these services, users are enduring the risk of leaking private information. Game theory is a powerful method that is utilized to balance such tradeoff problems. The drawback is that most schemes consider the tradeoff problem from the aspect of the users, while the platform is the party that dominates the interaction in reality. There is also an oversight to formulate the interaction occurring between multiple users, as well as the mutual influence between any two parties involved, including the user, platform and adversary. In this paper, we propose a platform-centric two-layer three-party game model to protect the users’ privacy and provide quality of service. One layer focuses on the interactions among the multiple asymmetric users and the second layer considers the influence between any two of the three parties (user, platform, and adversary). We prove that the Nash Equilibrium exists in the proposed game and find the optimal strategy for the platform to provide quality service, while protecting private data, along with interactions with the adversary. Using real datasets, we present simulations to validate our theoretical analysis.
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This work is partly supported by the National Science Foundation (NSF) under grant NOs. 1252292, 1741277, 1704287, and 1829674.
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Huang, Y., Cai, Z., Bourgeois, A.G. (2019). Privacy Protection for Context-Aware Services: A Two-Layer Three-Party Game Model. In: Biagioni, E., Zheng, Y., Cheng, S. (eds) Wireless Algorithms, Systems, and Applications. WASA 2019. Lecture Notes in Computer Science(), vol 11604. Springer, Cham. https://doi.org/10.1007/978-3-030-23597-0_10
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