Vector Dominance with Threshold Searchable Encryption (VDTSE) for the Internet of Things

Abstract

The Internet of Medical Things (IoMT) is an application of the Internet of Things (IoT) in the medical field. It is a cutting-edge technique that connects medical sensors and their applications to healthcare systems, which is essential in smart healthcare. However, Personal Health Records (PHRs) are normally kept in public cloud servers controlled by IoMT service providers, so privacy and security incidents may be frequent. Fortunately, Searchable Encryption (SE), which can be used to execute queries on encrypted data, can address the issue above. Nevertheless, most existing SE schemes cannot solve the vector dominance threshold problem. In response to this, we present a SE scheme called Vector Dominance with Threshold Searchable Encryption (VDTSE) in this study. We use a Lagrangian polynomial technique and convert the vector dominance threshold problem into a constraint that the number of two equal-length vectors’ corresponding bits excluding wildcards is not less than a threshold t. Then, we solve the problem using the proposed technique modified in Hidden Vector Encryption (HVE). This technique makes the trapdoor size linear to the number of attributes and thus much smaller than that of other similar SE schemes. A rigorous experimental analysis of a specific application for privacy-preserving diabetes demonstrates the feasibility of the proposed VDTSE scheme.