Achieving privacy protection for crowdsourcing application in edge-assistant vehicular networking

Hui Li (), Lishuang Pei (), Dan Liao (), Ming Zhang (), Du Xu () and Xiong Wang ()
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Hui Li: University of Electronic Science and Technology of China
Lishuang Pei: University of Electronic Science and Technology of China
Dan Liao: University of Electronic Science and Technology of China
Ming Zhang: University of Electronic Science and Technology of China
Du Xu: University of Electronic Science and Technology of China
Xiong Wang: University of Electronic Science and Technology of China

Telecommunication Systems: Modelling, Analysis, Design and Management, 2020, vol. 75, issue 1, No 1, 14 pages

Abstract: Abstract Crowdsourcing application, deemed as a key evolution on the way to vehicular networking, has great potential to provide real-time services. However, existing cloud-based vehicular networking cannot support real-time data transmission with wasting massive bandwidth resources. This paper studies the crowdsourcing application in edge-assistant vehicular networking. To improve the real-time demand of data transmission, we propose the E-node of that owns the learning and semantic analysis abilities. Then we analyze two data transmission scenarios of crowdsourcing for collected data: road map uploading, traffic accident and traffic flow. On the other hand, to address the privacy leakages in the process of data aggregation and data distribution, we separately design time-tolerance anonymous privacy protection algorithm and k − 1 location-offset privacy protection algorithm. Finally, we conduct extensive experiments to verify the effectiveness of our proposed privacy protection algorithms, including time delay, offset probability, privacy leakage probability and accuracy.

Keywords: Crowdsourcing; Vehicular networking; Edge-assistant; Privacy protection (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11235-020-00666-w

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