Efficient and privacy-preserving search in multi-source personal health record clouds

Personal Health Record (PHR) systems have been widely used to manage individuals´ medical history. Meanwhile, with a rapid growth of the volume of PHRs, individuals outsource PHR systems to the cloud to facilitate management. In this paper, we consider a multi-source cloud-based PHR environment, where hospitals as the data providers are authorized to upload an individual´s medical data to the cloud. In this environment, a data provider builds an index as an Multi-Dimensional B-tree from an individual´s medical data for fast lookup, and encrypts both the index and data before uploading, to preserve data privacy. To achieve efficient and privacy-preserving query on the encrypted medical data in cloud computing, we propose a Multi-source Encrypted Indexes Merging (MEIM) mechanism, where the indexes encrypted with a novel Multi-source Order-Preserving Symmetric Encryption (MOPSE) solution can be effectively merged by the cloud. The main merit of MEIM is that an individual only needs to issue one encrypted query to efficiently retrieve the PHRs of her interests, even if the indexes are encrypted under different symmetric keys. We prove that the query processing with MEIM for data user is n times faster than the tradition OPSE, where n denotes the number of data providers.