Achieving Efficient and Privacy-Preserving k -NN Query for Outsourced eHealthcare Data

摘要: The boom of Internet Things devices promotes huge volumes eHealthcare data will be collected and aggregated at provider. With the help these health data, provider can offer reliable service (e.g., k-NN query) to doctors for better diagnosis. However, IT facility in is incompetent with so one popular solution deploy a powerful cloud appoint execute query service. In this case, since are very sensitive yet servers not fully trusted, directly executing inevitably incurs privacy challenges. Apart from issues, efficiency issues also need taken into consideration because achieving requirement incur additional computational cost. existing focuses on do (fully) consider or inefficient. For instance, best complexity over encrypted as large $O(k\log ^{3} N)$ , where N total number data. paper, aiming addressing challenges, we design an efficient privacy-preserving scheme outsourced Our proposed characterized by integrating k d-tree homomorphic encryption technique storing processing Compared works, our more terms query. Specifically, achieve computation $O(lk\log complexity, l respectively denote dimension addition, detailed security analysis shows that really under model performance evaluation indicates indeed