A privacy mechanism for mobile commerce

In mobile commerce, a company provides location based services to a set of mobile users. The users report to the company their location with a level of granularity to maintain a degree of anonymity, depending on their perceived risk, and receive in return monetary benefits or better services from the company. This paper formulates a quantitative model in which information theoretic metrics such as entropy, quantify the anonymity level of the users. The individual perceived risks of users and the benefits they obtain are considered to be linear functions of their chosen location information granularity. The interaction between the mobile commerce company and its users are investigated using mechanism design techniques as a privacy game. The user best responses and optimal strategies for the company are derived under budgetary constraints on incentives, which are provided to users in order to convince them to share their private information at the desired level of granularity.