A Privacy-Preserving Fog Computing Framework for Vehicular Crowdsensing Networks
Recently, the study of road surface condition monitoring has drawn great attention to improve the traffic efficiency and road safety. As a matter of fact, this activity plays a critical role in the management of the transportation infrastructure. Trustworthiness and individual privacy affect the pra...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2018-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8423615/ |
| _version_ | 1818914492167225344 |
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| author | Jiannan Wei Xiaojie Wang Nan Li Guomin Yang Yi Mu |
| author_facet | Jiannan Wei Xiaojie Wang Nan Li Guomin Yang Yi Mu |
| author_sort | Jiannan Wei |
| collection | DOAJ |
| description | Recently, the study of road surface condition monitoring has drawn great attention to improve the traffic efficiency and road safety. As a matter of fact, this activity plays a critical role in the management of the transportation infrastructure. Trustworthiness and individual privacy affect the practical deployment of the vehicular crowdsensing network. Mobile sensing as well as the contemporary applications are made use of problem solving. The fog computing paradigm is introduced to meet specific requirements, including the mobility support, low latency, and location awareness. The fog-based vehicular crowdsensing network is an emerging transportation management infrastructure. Moreover, the fog computing is effective to reduce the latency and improve the quality of service. Most of the existing authentication protocols cannot help the drivers to judge a message when the authentication on the message is anonymous. In this paper, a fog-based privacy-preserving scheme is proposed to enhance the security of the vehicular crowdsensing network. Our scheme is secure with the security properties, including non-deniability, mutual authentication, integrity, forward privacy, and strong anonymity. We further analyze the designed scheme, which can not only guarantee the security requirements but also achieve higher efficiency with regards to computation and communication compared with the existing schemes. |
| first_indexed | 2024-12-19T23:47:14Z |
| format | Article |
| id | doaj.art-14cb4e98fec542878be7610a8a2719fd |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T23:47:14Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-14cb4e98fec542878be7610a8a2719fd2022-12-21T20:01:15ZengIEEEIEEE Access2169-35362018-01-016437764378410.1109/ACCESS.2018.28614308423615A Privacy-Preserving Fog Computing Framework for Vehicular Crowdsensing NetworksJiannan Wei0https://orcid.org/0000-0001-9288-1949Xiaojie Wang1Nan Li2Guomin Yang3Yi Mu4School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, ChinaSchool of Software, Dalian University of Technology, Dalian, ChinaCentre for Computer and Information Security Research, School of Computing and Information Technology, University of Wollongong, Wollongong, NSW, AustraliaCentre for Computer and Information Security Research, School of Computing and Information Technology, University of Wollongong, Wollongong, NSW, AustraliaSchool of Mathematics and Computer Science, Fujian Normal University, Fuzhou, ChinaRecently, the study of road surface condition monitoring has drawn great attention to improve the traffic efficiency and road safety. As a matter of fact, this activity plays a critical role in the management of the transportation infrastructure. Trustworthiness and individual privacy affect the practical deployment of the vehicular crowdsensing network. Mobile sensing as well as the contemporary applications are made use of problem solving. The fog computing paradigm is introduced to meet specific requirements, including the mobility support, low latency, and location awareness. The fog-based vehicular crowdsensing network is an emerging transportation management infrastructure. Moreover, the fog computing is effective to reduce the latency and improve the quality of service. Most of the existing authentication protocols cannot help the drivers to judge a message when the authentication on the message is anonymous. In this paper, a fog-based privacy-preserving scheme is proposed to enhance the security of the vehicular crowdsensing network. Our scheme is secure with the security properties, including non-deniability, mutual authentication, integrity, forward privacy, and strong anonymity. We further analyze the designed scheme, which can not only guarantee the security requirements but also achieve higher efficiency with regards to computation and communication compared with the existing schemes.https://ieeexplore.ieee.org/document/8423615/Fog computingcrowdsensing vehicular networksprivacy-preservingstrong anonymitynon-deniability |
| spellingShingle | Jiannan Wei Xiaojie Wang Nan Li Guomin Yang Yi Mu A Privacy-Preserving Fog Computing Framework for Vehicular Crowdsensing Networks IEEE Access Fog computing crowdsensing vehicular networks privacy-preserving strong anonymity non-deniability |
| title | A Privacy-Preserving Fog Computing Framework for Vehicular Crowdsensing Networks |
| title_full | A Privacy-Preserving Fog Computing Framework for Vehicular Crowdsensing Networks |
| title_fullStr | A Privacy-Preserving Fog Computing Framework for Vehicular Crowdsensing Networks |
| title_full_unstemmed | A Privacy-Preserving Fog Computing Framework for Vehicular Crowdsensing Networks |
| title_short | A Privacy-Preserving Fog Computing Framework for Vehicular Crowdsensing Networks |
| title_sort | privacy preserving fog computing framework for vehicular crowdsensing networks |
| topic | Fog computing crowdsensing vehicular networks privacy-preserving strong anonymity non-deniability |
| url | https://ieeexplore.ieee.org/document/8423615/ |
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