Abstract

With the development of cloud computing, the interest on spatial database outsourcing has been sharply increasing. Therefore, researches on data encryption methods for protecting location data privacy in outsourced databases have been actively performed. However, the existing data encryption schemes do not consider data distribution when generating data clusters and they use a tree-based index for processing k-nearest neighbor queries. As a result, the performance of query processing algorithm can fluctuate depending on the tree depth. To solve these problems, we propose a densityaware data encryption scheme and a query processing algorithm for database outsourcing. Our density-aware data encryption scheme uses a grid index to generate clusters and transforms the original data information into a bitmap. To provide efficient query processing, we use an algebraic coding based hash index to reduce the data retrieval time. Finally, in performance analysis, we show that the proposed scheme provides better query processing performance and guarantees the privacy of users, compared with the existing schemes.

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