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Open AccessArticle

A Privacy Preserving Cloud-Based K-NN Search Scheme with Lightweight User Loads

MediaTek Inc., Hsinchu 30078, Taiwan
Graduate Institute of Networking and Multimedia, National Taiwan University, Taipei 10617, Taiwan
Department of Computer Science and Information Engineering, National Taiwan University, Taipei 10617, Taiwan
Author to whom correspondence should be addressed.
Computers 2020, 9(1), 1;
Received: 4 November 2019 / Revised: 28 December 2019 / Accepted: 29 December 2019 / Published: 1 January 2020
With the growing popularity of cloud computing, it is convenient for data owners to outsource their data to a cloud server. By utilizing the massive storage and computational resources in cloud, data owners can also provide a platform for users to make query requests. However, due to the privacy concerns, sensitive data should be encrypted before outsourcing. In this work, a novel privacy preserving K-nearest neighbor (K-NN) search scheme over the encrypted outsourced cloud dataset is proposed. The problem is about letting the cloud server find K nearest points with respect to an encrypted query on the encrypted dataset, which was outsourced by data owners, and return the searched results to the querying user. Comparing with other existing methods, our approach leverages the resources of the cloud more by shifting most of the required computational loads, from data owners and query users, to the cloud server. In addition, there is no need for data owners to share their secret key with others. In a nutshell, in the proposed scheme, data points and user queries are encrypted attribute-wise and the entire search algorithm is performed in the encrypted domain; therefore, our approach not only preserves the data privacy and query privacy but also hides the data access pattern from the cloud server. Moreover, by using a tree structure, the proposed scheme could accomplish query requests in sub-liner time, according to our performance analysis. Finally, experimental results demonstrate the practicability and the efficiency of our method.
Keywords: K-NN; privacy preserving; cloud; encryption; security K-NN; privacy preserving; cloud; encryption; security
MDPI and ACS Style

Hsu, Y.-C.; Hsueh, C.-H.; Wu, J.-L. A Privacy Preserving Cloud-Based K-NN Search Scheme with Lightweight User Loads. Computers 2020, 9, 1.

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