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Title Vehicle-based secure location clustering for IoT-equipped building and facility management in smart city
ID_Doc 39156
Authors Wu, HP; Li, LL; Liu, Y; Wu, XT
Title Vehicle-based secure location clustering for IoT-equipped building and facility management in smart city
Year 2022
Published
DOI 10.1016/j.buildenv.2022.108937
Abstract Vehicles equipped with various sensing devices have the strong ability to generate location information, which is beneficial to a lot of applications in smart city. In special, it is important to take full advantage of the traffic information to manage the buildings and facilities with special services, including charging/gas stations, car parks and leisure centers. However, location data are outsourced to the third party (e.g., vehicles and the vehicular cloud), which causes high security risks. In this paper, we first define a personalized local differential privacy criterion for location data, which offers a strong private guarantee to drivers. Then, we propose a density-based location clustering mechanism, i.e., PLPP-CLIQUE, which not only satisfies the proposed privacy criterion but also maximizes the utility of vehicles for location-based services. Moreover, we design a more efficient mechanism, i.e., Improved-PLPP-CLIQUE, to increase the utility of location clustering for vehicular clouds under the same privacy requirement. We demonstrate that our mechanisms satisfy the privacy criterion and have the high utility by theoretical analysis. Finally, we perform extensive experiments to show the good capability of our mechanisms.
Author Keywords Location clustering; Privacy preservation; Utility optimization; Building and facility planning
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED)
EID WOS:000780322700001
WoS Category Construction & Building Technology; Engineering, Environmental; Engineering, Civil
Research Area Construction & Building Technology; Engineering
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