Efficient and Expressive Search Scheme over Encrypted Electronic Medical Records

Author:

Yang Xiaopei1,Zhang Yu1,Wang Yifan2,Li Yin3

Affiliation:

1. School of Computer and Information Technology, Xinyang Normal University, Xinyang 464031, China

2. Department of Computer Science, Wayne State University, 42 W Warren Ave, Detroit, MI 48202, USA

3. School of Cyberspace Security, Dongguan University of Technology, Dongguan 523820, China

Abstract

In recent years, there has been rapid development in computer technology, leading to an increasing number of medical systems utilizing electronic medical records (EMRs) to store their clinical data. Because EMRs are very private, healthcare institutions usually encrypt these data before transferring them to cloud servers. A technique known as searchable encryption (SE) can be used by healthcare institutions to encrypt EMR data. This technique enables searching within the encrypted data without the need for decryption. However, most existing SE schemes only support keyword or range searches, which are highly inadequate for EMR data as they contain both textual and digital content. To address this issue, we have developed a novel searchable symmetric encryption scheme called SSE-RK, which is specifically designed to support both range and keyword searches, and it is easily applicable to EMR data. We accomplish this by creating a conversion technique that turns keywords and ranges into vectors. These vectors are then used to construct index tree building and search algorithms that enable simultaneous range and keyword searches. We encrypt the index tree using a secure K-Nearest Neighbor technique, which results in an effective SSE-RK approach with a search complexity that is quicker than a linear approach. Theoretical and experimental study further demonstrates that our proposed scheme surpasses previous similar schemes in terms of efficiency. Formal security analysis demonstrates that SSE-RK protects privacy for both data and queries during the search process. Consequently, it holds significant potential for a wide range of applications in EMR data. Overall, our SSE-RK scheme, which offers improved functionality and efficiency while protecting the privacy of EMR data, generally solves the shortcomings of the current SE schemes.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Henan

Nanhu Scholars Program for Young Scholars of XYNU

Publisher

MDPI AG

Subject

Information Systems

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