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...

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Main Authors: Jiannan Wei, Xiaojie Wang, Nan Li, Guomin Yang, Yi Mu
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8423615/
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spelling doaj-14cb4e98fec542878be7610a8a2719fd2021-03-29T20:51:00ZengIEEEIEEE 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
collection DOAJ
language English
format Article
sources DOAJ
author Jiannan Wei
Xiaojie Wang
Nan Li
Guomin Yang
Yi Mu
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
author_facet Jiannan Wei
Xiaojie Wang
Nan Li
Guomin Yang
Yi Mu
author_sort Jiannan Wei
title A Privacy-Preserving Fog Computing Framework for Vehicular Crowdsensing Networks
title_short 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_sort privacy-preserving fog computing framework for vehicular crowdsensing networks
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2018-01-01
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.
topic Fog computing
crowdsensing vehicular networks
privacy-preserving
strong anonymity
non-deniability
url https://ieeexplore.ieee.org/document/8423615/
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