A Negotiation Game: Establishing Stable Privacy Policies for Aggregate Reasoning

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The process of personal information collection and exchange is associated with ever-growing privacy concerns. To resolve the issue, data provider's consent on the usage of private information is sought through privacy policy speci cations. The parameters of such privacy policies in uence the quantity and quality of gathered information. Choosing the right privacy policy parameters can potentially increase the revenues to a data collector and the rms (third-parties) interested in accessing the database for data analysis purposes. In this work we use an extensive form game model to examine the decisions made by a data collector and a third-party to maximize their bene ts from collecting and accessing data. We have found the game's subgame perfect equilibria for various problem settings and provide the details of game analysis for a simpli ed scenario and two case studies. The equilibrium solutions demonstrate steady states of the game where collecting personal information at a speci c privacy level is advantageous to the data collector and the third-party. Consequently the results de ne a realistic boundary on collecting personal information.
Game Theory, Data Privacy