Abstract
With the proliferation of location-aware mobile devices and the prevalence of wireless communications, location-based services (LBS) have attracted much particular attention in recent years. For flexibility and cost savings, the LBS provider outsources the LBS data to the cloud in order to serve the increasing number of mobile users. To guarantee users’ privacy and data confidentiality, some excellent works have been proposed which focus on secure query over the location server. However, these existing works have two limitations. On the one hand, they cannot preserve users’ location and query content privacy simultaneously. On the other hand, they fail to support multi-keyword queries. In this article, aiming at a multi-keywords query in LBS, we propose a novel efficient and privacy-preserving multi-keyword query scheme (PPMQ) over the outsourced cloud, which satisfies the requirements of the location and query content privacy protection, query efficiency, the confidentiality of LBS data and scalability regarding the data users. To improve the efficiency of our proposed scheme, we utilize the linear quad-tree technique to build a grid system to represent the location information in the query condition as well as a searchable index. To protect the location privacy, we combine decimal Morton code and public-key cryptography techniques to build a searchable index or to generate a trapdoor. To enable the cloud server to perform a secure multi-keyword query, we systematically construct a privacy-preserving query scheme with bilinear pairing-based cryptography. In particular, our proposed scheme is scalable and very suitable for multi-user environments due to the flexible user registration and revocation mechanisms. Furthermore, a detailed security analysis shows that the proposed scheme can ensure the confidentiality of LBS data, and protect the location and query content privacy. Extensive experiments are conducted on a real LBS dataset, and the simulation results confirm the security and efficiency of our scheme.
Highlights
With the proliferation of wireless communication technologies and mobile devices with positioning capabilities, location-based services (LBS) are being extensively used in our daily life
We develop a fine-grained query protocol, where the data user can query the points of interest (POIs) by initiating a multi-keyword query and obtaining the desirable POIs according to their preference
Motivated by multi-keyword search in could computing, we focus on the secure multi-keyword query in LBS, enabling the LBS provider to return the most relevant POIs to query users accurately
Summary
With the proliferation of wireless communication technologies and mobile devices with positioning capabilities, location-based services (LBS) are being extensively used in our daily life. Different from existing works, aiming at the challenges as mentioned above, we propose an efficient privacy-preserving multi-keyword query scheme in LBS, named PPMQ, which provides fine-grained queries and returns more accurate POIs to users without divulging users’ sensitive information to both the cloud server or to other unregistered users. We propose a privacy-preserving multi-keyword query protocol in LBS, which enables the data user to obtain the desirable POIs more accurately and more conveniently without divulging the location and the query content privacy. C. DESIGN GOAL 1) Security Guarantee: The proposed scheme should prevent the cloud server from inferring the accurate location of users, user’s query content, and the actual contents and keywords value of encrypted poi records stored in the cloud.
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