Secure k-NN as a Service over Encrypted Data in Multi-User Setting

Abstract

To securely leverage the advantages of Cloud Computing, recently a lot of research has happened in the area of "Secure Query Processing over Encrypted Data". As a concrete use case, many encryption schemes have been proposed for securely processing k Nearest Neighbors (SkNN) over encrypted data in the outsourced setting. Recently Zhu et al. [25] proposed a SkNN solution which claimed to satisfy following four properties: (1)Data Privacy, (2)Key Confidentiality, (3)Query Privacy, and (4)Query Controllability. However, in this paper, we present an attack which breaks the Query Controllability claim of their scheme. Further, we propose a new SkNN solution which satisfies all the four existing properties along with an additional essential property of Query Check Verification. We analyze the security of our proposed scheme and present the detailed experimental results to showcase the efficiency in real world scenario.

Secure Hypersphere Range Query on Encrypted Data

“…Schemes by Zhu et al [44,45] and Singh et al [36] presented the solutions in multi-user setting. They considered the Query Privacy metric in their solutions, so that Query Users query is not known to Data owner and Cloud server.…”