Identifying Privacy Risks raised by Utility Queries
Résumé
Personal data are increasingly disseminated over the Web through mobile devices and smart environments, and are exploited for developing more and more sophisticated services and applications. All these advances come with serious risks for privacy breaches that may reveal private information wanted to remain undisclosed by data producers. It is therefore of utmost importance to help them to identify privacy risks raised by requests of service providers for utility purposes. In this paper, we first formalize privacy risks by privacy queries expressed (and kept secret) by each data producer to specify the data they do not want to be disclosed. Then, we develop a formal approach for detecting incompatibility between privacy and utility queries expressed as temporal aggregate conjunctive queries. The distinguishing point of our approach is to be data-independent and to come with an explanation based on the query expressions only. This explanation is intended to help data producers understand the detected privacy breaches and guide their choice of the appropriate technique to correct it.
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