TY - JOUR
T1 - Security and privacy preservation in fog-based crowd sensing on the internet of vehicles
AU - Sun, Gang
AU - Sun, Siyu
AU - Sun, Jian
AU - Yu, Hongfang
AU - Du, Xiaojiang
AU - Guizani, Mohsen
N1 - Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/5/15
Y1 - 2019/5/15
N2 - The emergence of fog computing enables fog-based vehicle crowd sensing (FBVC) to be utilized in various fields. However, existing privacy issues represent a primary challenge that limits the degree of participation by vehicles. To meet the demands of both data providers and users for privacy preservation and data validity, our work introduces a means for smart vehicles to partake in data crowd sensing while maintaining security and privacy, which includes privacy preservation, data aggregation, and traceability in a proposed data collection approach based on a heterogeneous two-tier fog architecture. These are three properties that prior attempts cannot all achieve. Moreover, a new scheme for trust authority (TA) security queries in fog computing to obtain outsourced encrypted map lists (MPLs) of the participants to achieve online traceability and identity retrieval for malicious participants is proposed in our study, which can reduce the storage burden of TA. Finally, the simulation results demonstrate the efficiency of our approach both in computation and communication.
AB - The emergence of fog computing enables fog-based vehicle crowd sensing (FBVC) to be utilized in various fields. However, existing privacy issues represent a primary challenge that limits the degree of participation by vehicles. To meet the demands of both data providers and users for privacy preservation and data validity, our work introduces a means for smart vehicles to partake in data crowd sensing while maintaining security and privacy, which includes privacy preservation, data aggregation, and traceability in a proposed data collection approach based on a heterogeneous two-tier fog architecture. These are three properties that prior attempts cannot all achieve. Moreover, a new scheme for trust authority (TA) security queries in fog computing to obtain outsourced encrypted map lists (MPLs) of the participants to achieve online traceability and identity retrieval for malicious participants is proposed in our study, which can reduce the storage burden of TA. Finally, the simulation results demonstrate the efficiency of our approach both in computation and communication.
KW - Crowd sensing
KW - Data aggregation
KW - Fog computing
KW - Internet of vehicles
KW - Privacy preservation
UR - http://www.scopus.com/inward/record.url?scp=85062462765&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85062462765&partnerID=8YFLogxK
U2 - 10.1016/j.jnca.2019.02.018
DO - 10.1016/j.jnca.2019.02.018
M3 - Article
AN - SCOPUS:85062462765
SN - 1084-8045
VL - 134
SP - 89
EP - 99
JO - Journal of Network and Computer Applications
JF - Journal of Network and Computer Applications
ER -