Achieving local differential location privacy protection in 3D space via Hilbert encoding and optimized random response
The widespread use of spatial location-based services not only provides considerable convenience, but also exposes the downsides of location privacy leakage. Most of the existing user-side location privacy protection techniques are limited to planar locations. However, the extensive use of aircraft,...
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| Format: | Article |
| Language: | English |
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Springer
2024-07-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157824001745 |
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| _version_ | 1849308140490719232 |
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| author | Yan Yan Pengbin Yan Adnan Mahmood Yang Zhang Quan Z. Sheng |
| author_facet | Yan Yan Pengbin Yan Adnan Mahmood Yang Zhang Quan Z. Sheng |
| author_sort | Yan Yan |
| collection | DOAJ |
| description | The widespread use of spatial location-based services not only provides considerable convenience, but also exposes the downsides of location privacy leakage. Most of the existing user-side location privacy protection techniques are limited to planar locations. However, the extensive use of aircraft, sensor equipment and acquisition devices with positioning functions promotes the urgency of protecting the privacy of 3D spatial locations. Therefore, this study suggests a local differential privacy protection approach for 3D spatial locations. A 3D spatial decomposition and Hilbert encoding method are designed to reduce the 3D location data into one-dimensional encoding. The optimized random response mechanism was utilized to perturb the dimensional-reduced location encoding, which not only achieves user-side location privacy protection but also improves the accuracy of aggregated data on the server-side. Experiments on the real spatial location datasets show that the suggested method can reduce spatial location service quality loss, maintain the availability of perturbed spatial location and improve the operation efficiency of the spatial location perturbation algorithm. |
| format | Article |
| id | doaj-art-143384d6beea4654bf819bbb105d5a24 |
| institution | Kabale University |
| issn | 1319-1578 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | Springer |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj-art-143384d6beea4654bf819bbb105d5a242025-08-20T03:54:33ZengSpringerJournal of King Saud University: Computer and Information Sciences1319-15782024-07-0136610208510.1016/j.jksuci.2024.102085Achieving local differential location privacy protection in 3D space via Hilbert encoding and optimized random responseYan Yan0Pengbin Yan1Adnan Mahmood2Yang Zhang3Quan Z. Sheng4School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, ChinaSchool of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, China; Corresponding author.School of Computing, Faculty of Science and Engineering, Macquarie University, Sydney, NSW 2109, AustraliaSchool of Information Management, Wuhan University, Wuhan, 430000, China; School of Computing, Faculty of Science and Engineering, Macquarie University, Sydney, NSW 2109, AustraliaSchool of Computing, Faculty of Science and Engineering, Macquarie University, Sydney, NSW 2109, AustraliaThe widespread use of spatial location-based services not only provides considerable convenience, but also exposes the downsides of location privacy leakage. Most of the existing user-side location privacy protection techniques are limited to planar locations. However, the extensive use of aircraft, sensor equipment and acquisition devices with positioning functions promotes the urgency of protecting the privacy of 3D spatial locations. Therefore, this study suggests a local differential privacy protection approach for 3D spatial locations. A 3D spatial decomposition and Hilbert encoding method are designed to reduce the 3D location data into one-dimensional encoding. The optimized random response mechanism was utilized to perturb the dimensional-reduced location encoding, which not only achieves user-side location privacy protection but also improves the accuracy of aggregated data on the server-side. Experiments on the real spatial location datasets show that the suggested method can reduce spatial location service quality loss, maintain the availability of perturbed spatial location and improve the operation efficiency of the spatial location perturbation algorithm.http://www.sciencedirect.com/science/article/pii/S1319157824001745Location privacy3D spatial locationLocal differential privacy3D Hilbert encodingOptimized random response |
| spellingShingle | Yan Yan Pengbin Yan Adnan Mahmood Yang Zhang Quan Z. Sheng Achieving local differential location privacy protection in 3D space via Hilbert encoding and optimized random response Journal of King Saud University: Computer and Information Sciences Location privacy 3D spatial location Local differential privacy 3D Hilbert encoding Optimized random response |
| title | Achieving local differential location privacy protection in 3D space via Hilbert encoding and optimized random response |
| title_full | Achieving local differential location privacy protection in 3D space via Hilbert encoding and optimized random response |
| title_fullStr | Achieving local differential location privacy protection in 3D space via Hilbert encoding and optimized random response |
| title_full_unstemmed | Achieving local differential location privacy protection in 3D space via Hilbert encoding and optimized random response |
| title_short | Achieving local differential location privacy protection in 3D space via Hilbert encoding and optimized random response |
| title_sort | achieving local differential location privacy protection in 3d space via hilbert encoding and optimized random response |
| topic | Location privacy 3D spatial location Local differential privacy 3D Hilbert encoding Optimized random response |
| url | http://www.sciencedirect.com/science/article/pii/S1319157824001745 |
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