An Efficient Privacy-Preserving Multi-Keyword Query Scheme in Location Based Services
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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9173763/ |
| _version_ | 1818928747715231744 |
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| author | Shiwen Zhang Tingting Yao Wei Liang Voundi Koe Arthur Sandor Kuan-Ching Li |
| author_facet | Shiwen Zhang Tingting Yao Wei Liang Voundi Koe Arthur Sandor Kuan-Ching Li |
| author_sort | Shiwen Zhang |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-20T03:33:50Z |
| format | Article |
| id | doaj.art-7c1e7bb80e614bdaabcae3e848c8302d |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-20T03:33:50Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-7c1e7bb80e614bdaabcae3e848c8302d2022-12-21T19:54:56ZengIEEEIEEE Access2169-35362020-01-01815403615404910.1109/ACCESS.2020.30184179173763An Efficient Privacy-Preserving Multi-Keyword Query Scheme in Location Based ServicesShiwen Zhang0https://orcid.org/0000-0003-2490-8171Tingting Yao1Wei Liang2https://orcid.org/0000-0002-5074-1363Voundi Koe Arthur Sandor3Kuan-Ching Li4https://orcid.org/0000-0003-1381-4364College of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, ChinaHunan Provincial Key Laboratory of Network Investigational Technology, Hunan Police Academy, Changsha, ChinaCollege of Computer Science and Electronic Engineering, Hunan University, Changsha, ChinaCollege of Computer Science and Electronic Engineering, Hunan University, Changsha, ChinaDepartment of Computer Science and Information Engineering, Providence University, Taichung, TaiwanWith 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.https://ieeexplore.ieee.org/document/9173763/Multi-keyword querylocation-based serviceslinear quad-treebilinear pairing map |
| spellingShingle | Shiwen Zhang Tingting Yao Wei Liang Voundi Koe Arthur Sandor Kuan-Ching Li An Efficient Privacy-Preserving Multi-Keyword Query Scheme in Location Based Services IEEE Access Multi-keyword query location-based services linear quad-tree bilinear pairing map |
| title | An Efficient Privacy-Preserving Multi-Keyword Query Scheme in Location Based Services |
| title_full | An Efficient Privacy-Preserving Multi-Keyword Query Scheme in Location Based Services |
| title_fullStr | An Efficient Privacy-Preserving Multi-Keyword Query Scheme in Location Based Services |
| title_full_unstemmed | An Efficient Privacy-Preserving Multi-Keyword Query Scheme in Location Based Services |
| title_short | An Efficient Privacy-Preserving Multi-Keyword Query Scheme in Location Based Services |
| title_sort | efficient privacy preserving multi keyword query scheme in location based services |
| topic | Multi-keyword query location-based services linear quad-tree bilinear pairing map |
| url | https://ieeexplore.ieee.org/document/9173763/ |
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