BPMS: Blockchain-Based Privacy-Preserving Multi-Keyword Search in Multi-Owner Setting

Searchable encryption (SE) has emerged as a cryptographic primitive that allows data users to search on encrypted data. Most existing SE schemes usually delegate search operations to an intermediary such as a cloud server, which would inevitably result in single-point failure, privacy leakage, and even untrustworthy results. Several blockchain-based SE schemes have been proposed to alleviate these issues; however, they suffer from some issues, such as the support for multi-keyword multi-owner model, query privacy and data storage availability. In this paper, we propose BPMS, blockchain-based privacy-preserving multi-keyword search in multi-owner setting, which supports searching over encrypted data in trustworthy, private and efficient manners. The attribute Bloom filter has been introduced into our BPMS to build indexes, which protects query privacy and improves index generation performance. To guarantee data storage availability, our BPMS leverages the advantages of IPFS (InterPlanetary File System) to store large scale of encrypted data. Security proof and comparative analysis in theory indicate that our BPMS is more secure and efficient. A series of experiments conducted on a real-world dataset further demonstrate that our BPMS is feasible in practice.

1 Introduction

With the prosperity of the Internet and cloud storage, outsourcing large-scale data to an intermediary such as a cloud server has been a popular paradigm for minimizing local data storage and maintenance burden [1]. However, due to the separation of data ownership and data control, it would suffer from various issues, such as privacy leakage, unauthorized access, illegal tampering and deletion [2]. The most common way is to encrypt the data before outsourcing, which would subsequently raise the critical issue of how to search on encrypted data. Searchable encryption (SE) as a promising, cryptographic primitive has emerged, which guarantees data confidentiality while not sacrificing searchability [3], [4]. Specifically, there are three entities in a typical SE system, where a data owner (DO) extracts a set of keywords, encrypts them into indexes and sends them with the encrypted data to a cloud server (CS), and then a data user (DU) creates a trapdoor associated with the query keywords and submits it to the CS responsible for searching. Nowadays, SE has been widely used in various fields such as healthcare [5], smart grid [6], and the Internet of Things [7].