Article ID Journal Published Year Pages File Type
379566 Electronic Commerce Research and Applications 2016 13 Pages PDF
Abstract

•A privacy-preserving service framework for the mobile commerce alliance providing location-based services.•Definitions of personalized privacy profile of the mobile user and the (K, L, P)-anonymity model.•A new privacy-preserving algorithm named EMAGAS, which features the construction of minimal initial K-anonymity sets, an exchanging process and a merging process.•Experimental validation of the feasibility and the performance advantages of EMAGAS based on a real road network and generated privacy profiles of mobile users.

The risk of privacy disclosure in mobile commerce has received increasing attention worldwide. Although many papers related to information privacy and privacy-preserving technologies exist, few are based on a particular mobile commerce model to study the anonymity models and privacy-preserving algorithms. A privacy-preserving service framework for the mobile commerce alliance providing location-based services is established. According to the defined personalized privacy profile of the mobile user, a (K, L, P)-anonymity model is formally described. Based on the model, a new privacy-preserving algorithm for exchanging and merging processes for generating anonymity sets (EMAGAS) is proposed, which features the construction of minimal initial K-anonymity sets, an exchanging process and a merging process. The processes of exchanging and merging are formally described. EMAGAS can be used to protect the location, identifier and other sensitive information of the mobile user on a road network. The availability of EMAGAS is illustrated by an example. Finally, based on a real road network and generated privacy profiles of mobile users, the feasibility and advantages of EMAGAS are experimentally validated.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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