Open Access

ARTICLE

Privacy-Preserving Multi-Keyword Fuzzy Adjacency Search Strategy for Encrypted Graph in Cloud Environment

Bin Wu^1,2, Xianyi Chen³, Jinzhou Huang^4,*, Caicai Zhang⁵, Jing Wang⁶, Jing Yu^1,2, Zhiqiang Zhao⁷, Zhuolin Mei^1,2

1 School of Computer and Big Data Science, Jiujiang University, Jiujiang, 332005, China
2 Jiujiang Key Laboratory of Network and Information Security, Jiujiang, 332005, China
3 School of Computer and Software, Nanjing University of Information Science & Technology, Nanjing, 210044, China
4 School of Computer Engineering, Hubei University of Arts and Science, Xiangyang, 441053, China
5 School of Modern Information Technology, Zhejiang Institute of Mechanical and Electrical Engineering, Hangzhou, 310053, China
6 Information Center, Jiangxi Changjiang Chemical Co., Ltd., Jiujiang, 332005, China
7 School of Mathematics and Computer Science, Ningxia Normal University, Guyuan, 756099, China

* Corresponding Author: Jinzhou Huang. Email:

Computers, Materials & Continua 2024, 78(3), 3177-3194. https://doi.org/10.32604/cmc.2023.047147

Received 26 October 2023; Accepted 15 December 2023; Issue published 26 March 2024

Abstract

In a cloud environment, outsourced graph data is widely used in companies, enterprises, medical institutions, and so on. Data owners and users can save costs and improve efficiency by storing large amounts of graph data on cloud servers. Servers on cloud platforms usually have some subjective or objective attacks, which make the outsourced graph data in an insecure state. The issue of privacy data protection has become an important obstacle to data sharing and usage. How to query outsourcing graph data safely and effectively has become the focus of research. Adjacency query is a basic and frequently used operation in graph, and it will effectively promote the query range and query ability if multi-keyword fuzzy search can be supported at the same time. This work proposes to protect the privacy information of outsourcing graph data by encryption, mainly studies the problem of multi-keyword fuzzy adjacency query, and puts forward a solution. In our scheme, we use the Bloom filter and encryption mechanism to build a secure index and query token, and adjacency queries are implemented through indexes and query tokens on the cloud server. Our proposed scheme is proved by formal analysis, and the performance and effectiveness of the scheme are illustrated by experimental analysis. The research results of this work will provide solid theoretical and technical support for the further popularization and application of encrypted graph data processing technology.

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Keywords

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