TY - JOUR
T1 - Privacy for 5G-Supported Vehicular Networks
AU - Li, Meng
AU - Zhu, Liehuang
AU - Zhang, Zijian
AU - Lal, Chhagan
AU - Conti, Mauro
AU - Martinelli, Fabio
PY - 2021
Y1 - 2021
N2 - Vehicular networks allow billions of vehicular users to be connected to report and exchange real-time data for offering various services, such as navigation, ride-hailing, smart parking, traffic monitoring, and vehicular digital forensics. Fifth generation (5G) is a new radio access technology with greater coverage, accessibility, and higher network density. 5G-supported Vehicular Networks (5GVNs) have attracted plenty of attention from both academia and industry. Geared with new features, they are expected to revolutionize the mobility ecosystem to empower a portfolio of new services. Meanwhile, the development of such communication capabilities, along with the development of sensory devices and the enhancement of local computing powers, have lead to an inevitable reality of massive data (e.g., identity, location, and trajectory) collection from vehicular users. Unfortunately, 5GVN are still confronted with a variety of privacy threats. Such threats are targeted at users’ data, identity, location, and trajectory. If not properly handled, such threats will cause unimaginable consequences to users. In this survey, we first review the state-of-the-art of survey papers. Next, we introduce the architecture, features, and services of 5GVN, followed by the privacy objectives of 5GVN and privacy threats to 5GVN. Further, we present existing privacy-preserving solutions and analyze them in-depth. Finally, we define some future research directions to draw more attention and down-to-earth efforts into this new architecture and its privacy issues.
AB - Vehicular networks allow billions of vehicular users to be connected to report and exchange real-time data for offering various services, such as navigation, ride-hailing, smart parking, traffic monitoring, and vehicular digital forensics. Fifth generation (5G) is a new radio access technology with greater coverage, accessibility, and higher network density. 5G-supported Vehicular Networks (5GVNs) have attracted plenty of attention from both academia and industry. Geared with new features, they are expected to revolutionize the mobility ecosystem to empower a portfolio of new services. Meanwhile, the development of such communication capabilities, along with the development of sensory devices and the enhancement of local computing powers, have lead to an inevitable reality of massive data (e.g., identity, location, and trajectory) collection from vehicular users. Unfortunately, 5GVN are still confronted with a variety of privacy threats. Such threats are targeted at users’ data, identity, location, and trajectory. If not properly handled, such threats will cause unimaginable consequences to users. In this survey, we first review the state-of-the-art of survey papers. Next, we introduce the architecture, features, and services of 5GVN, followed by the privacy objectives of 5GVN and privacy threats to 5GVN. Further, we present existing privacy-preserving solutions and analyze them in-depth. Finally, we define some future research directions to draw more attention and down-to-earth efforts into this new architecture and its privacy issues.
KW - Vehicular networks
KW - 5G
KW - privacy
KW - privacy-preserving solutions
UR - http://www.scopus.com/inward/record.url?scp=85135555101&partnerID=8YFLogxK
U2 - 10.1109/OJCOMS.2021.3103445
DO - 10.1109/OJCOMS.2021.3103445
M3 - Article
SN - 2644-125X
VL - 2
SP - 1935
EP - 1956
JO - IEEE Open Journal of the Communications Society
JF - IEEE Open Journal of the Communications Society
M1 - 9511636
ER -