Trace Your Footprint: Efficient Spatial Keyword Query Over Encrypted Trajectory Data
With the popularity of mobile devices, spatial-textual trajectory query has been deployed in applications such as trajectory-based navigation and travel route recommendation. Massive trajectory data have been outsourced to cloud servers for storage and sharing such as spatial keyword search. However...
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| Vydáno v: | IEEE transactions on information forensics and security Ročník 20; s. 11936 - 11949 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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IEEE
2025
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| ISSN: | 1556-6013, 1556-6021 |
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| Abstract | With the popularity of mobile devices, spatial-textual trajectory query has been deployed in applications such as trajectory-based navigation and travel route recommendation. Massive trajectory data have been outsourced to cloud servers for storage and sharing such as spatial keyword search. However, existing solutions only support similarity queries in the spatial dimension and still incur high storage and query costs, which cannot scale well in large-scale trajectory data scenarios. To solve the above issues, we first achieve an Efficient Range Query over Encrypted Trajectory Data (<inline-formula> <tex-math notation="LaTeX">\textsf {ERT} </tex-math></inline-formula>) using Douglas-Peucker trajectory compression algorithm, random matrix multiplication, filtering-verification mechanism and polynomial fitting technology. Then, we further propose an enhanced Efficient Spatial Keyword Query over Encrypted Trajectory Data (<inline-formula> <tex-math notation="LaTeX">\textsf {ESKT} </tex-math></inline-formula>) by constructing a unified spatial-textual index structure, which can find relevant trajectories that are within some arbitrary geometric range and contain all query keywords. Finally, we formally prove that our schemes are secure against chosen-plaintext-attack, and conduct extensive experiments to demonstrate that our schemes improve the query efficiency by almost <inline-formula> <tex-math notation="LaTeX">100\times </tex-math></inline-formula> when compared with state-of-the-art solutions. |
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| AbstractList | With the popularity of mobile devices, spatial-textual trajectory query has been deployed in applications such as trajectory-based navigation and travel route recommendation. Massive trajectory data have been outsourced to cloud servers for storage and sharing such as spatial keyword search. However, existing solutions only support similarity queries in the spatial dimension and still incur high storage and query costs, which cannot scale well in large-scale trajectory data scenarios. To solve the above issues, we first achieve an Efficient Range Query over Encrypted Trajectory Data (<inline-formula> <tex-math notation="LaTeX">\textsf {ERT} </tex-math></inline-formula>) using Douglas-Peucker trajectory compression algorithm, random matrix multiplication, filtering-verification mechanism and polynomial fitting technology. Then, we further propose an enhanced Efficient Spatial Keyword Query over Encrypted Trajectory Data (<inline-formula> <tex-math notation="LaTeX">\textsf {ESKT} </tex-math></inline-formula>) by constructing a unified spatial-textual index structure, which can find relevant trajectories that are within some arbitrary geometric range and contain all query keywords. Finally, we formally prove that our schemes are secure against chosen-plaintext-attack, and conduct extensive experiments to demonstrate that our schemes improve the query efficiency by almost <inline-formula> <tex-math notation="LaTeX">100\times </tex-math></inline-formula> when compared with state-of-the-art solutions. |
| Author | Li, Xinghua Miao, Yinbin Wang, Xin Xu, Shujiang Deng, Robert H. Liu, Zhiquan Zhang, Shu Raymond Choo, Kim-Kwang |
| Author_xml | – sequence: 1 givenname: Yinbin orcidid: 0000-0001-5437-3572 surname: Miao fullname: Miao, Yinbin email: ybmiao@xidian.edu.cn organization: School of Cyber Engineering, Xidian University, Xi'an, China – sequence: 2 givenname: Xin orcidid: 0009-0002-3354-9342 surname: Wang fullname: Wang, Xin email: wxsenator@163.com organization: School of Cyber Engineering, Xidian University, Xi'an, China – sequence: 3 givenname: Shu orcidid: 0009-0007-9690-335X surname: Zhang fullname: Zhang, Shu email: zhangshu0108@163.com organization: School of Cyber Engineering, Xidian University, Xi'an, China – sequence: 4 givenname: Xinghua orcidid: 0000-0002-5583-4155 surname: Li fullname: Li, Xinghua email: xhli1@mail.xidian.edu.cn organization: State Key Laboratory of Integrated Service Networks, School of Cyber Engineering, Xidian University, Xi'an, China – sequence: 5 givenname: Shujiang orcidid: 0000-0001-9151-2834 surname: Xu fullname: Xu, Shujiang email: xushj@sdas.org organization: Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China – sequence: 6 givenname: Zhiquan orcidid: 0000-0002-3934-2177 surname: Liu fullname: Liu, Zhiquan email: zqliu@vip.qq.com organization: College of Cyber Security, Jinan University, Guangzhou, China – sequence: 7 givenname: Kim-Kwang orcidid: 0000-0001-9208-5336 surname: Raymond Choo fullname: Raymond Choo, Kim-Kwang email: raymond.choo@fulbrightmail.org organization: Department of Information Systems and Cyber Security, The University of Texas at San Antonio, San Antonio, TX, USA – sequence: 8 givenname: Robert H. orcidid: 0000-0003-3491-8146 surname: Deng fullname: Deng, Robert H. email: robertdeng@smu.edu.sg organization: School of Information Systems, Singapore Management University, Bras Basah, Singapore |
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| SubjectTerms | Accuracy Costs Electronic mail Encryption Filtering algorithms filtering-verification mechanism Fitting Indexes Polynomials Spatial databases spatial keyword query spatial-textual index structure Trajectory trajectory compression Trajectory query |
| Title | Trace Your Footprint: Efficient Spatial Keyword Query Over Encrypted Trajectory Data |
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