Reliable and Privacy-preserving Task Recomposition for Crowdsensing in Vehicular Fog Computing

被引:0
作者
Wang, Biying [1 ]
Chang, Zheng [1 ]
Zhou, Zhenyu [2 ]
Ristaniemi, Tapani [1 ]
机构
[1] Univ Jyvaskyla, Fac Informat Technol, POB 35, FI-40014 Jyvaskyla, Finland
[2] North China Elect Power Univ, Sch Elect & Elect Engn, Beijing, Peoples R China
来源
2018 IEEE 87TH VEHICULAR TECHNOLOGY CONFERENCE (VTC SPRING) | 2018年
关键词
Task recomposition; privacy-preserving; crowd sensing; report; vehicular fog computing;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The advancement in vehicles has enabled crowd sensing in vehicular fog computing (VFC), where vehicles are recruited to be assigned different subtasks and participate sensing activities that may disclose their sensitive information. To stimulate more participants, VFC systems should be able to provide reliable and privacy-preserving data transmission and processing mechanisms for the sensing report. To ensure the report process, we present a reliable and privacy-preserving task recomposition (REPTAR) for multiple subtasks sensing in VFC. Modified homomorphic Paillier encryption and superincreasing sequence are employed for aggregating hybrid subtasks into one ciphertext. Reliability is verified by means and variances of each aggregated subtasks from different vehicular fog nodes. Detailed security analysis and performance evaluation are provided to demonstrate the security, privacy-enhancement, efficiency and low complexity of the proposed REPTAR.
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页数:6
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