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Strengthening data privacy during propagation

More and more smartphone applications need microdata, but publishing a microdata table may leak respondents' privacy. Conventional research on Privacy Preserving Data Publishing (PPDP) focuses on providing an identical privacy protection. Consider that, instead of being trapped in a small coterie, information usually propagates from friend to friend. In this paper, we study the PPDP problem on a mobile social network: along a table's propagation path, how can we create a series of tables with increasing privacy protection levels? The tradeoff between the created tables' overall utility and their individual privacy requirements are not trivial, especially for distributed systems: any inappropriate sanitization operation under a lower privacy-level may cause dramatic utility loss on subsequent tables. In order to solve the problem, we propose an approximation algorithm by previewing the future privacy requirements. Simulation results show that our scheme can successfully increase the overall utility, and meet the strengthening privacy protection requirements.