There has been a tremendous growth in health data collection since the development of Electronic Medical Record (EMR) systems. Such collected data is further shared and analyzed for diverse purposes. Despite many benefits, data collection and sharing have become a big concern as it threatens individual privacy. In this paper, we propose a secure and private data management framework that addresses both the security and privacy issues in the management of medical data in outsourced databases. The proposed framework ensures the security of data by using semantically-secure encryption schemes to keep data encrypted in outsourced databases. The framework also provides a differentially-private query interface that can support a number of SQL queries and complex data mining tasks. We experimentally evaluate the performance of the proposed framework, and the results show that the proposed framework is practical and has low overhead.

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International audiencePersonal Health Records (PHR) are user-friendly, online solutions that give patients a way of managing their own health information. Many of the current PHR systems allow storage providers to access patients’ data. Recently, architectures of storing PHRs in cloud have been proposed. However, privacy remains a major issue for patients. Consequently, it is a promising method to encrypt PHRs before outsourcing. Encrypting PHRs prevents health organizations from analyzing medical data. In this paper, we propose a protocol that would allow health organizations to produce statistical information about encrypted PHRs stored in the cloud. The protocol depends on two threshold homomorphic cryptosystems: Goldwasser-Micali (GM) and Paillier. It executes queries on Kd-trees that are constructed from encrypted health records. It also prevents patients from inferring what health organizations are concerned about. We experimentally evaluate the performance of the proposed protocol and report on the results of implementation