Secure and Reliable Slicing in 5G and Beyond Vehicular Networks

被引:20
|
作者
Wang, Jiadai [1 ]
Liu, Jiajia [2 ]
机构
[1] Northwestern Polytech Univ, Xian, Shaanxi, Peoples R China
[2] Northwestern Polytech Univ, Sch Cybersecur, Xian, Shaanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
5G mobile communication; Network slicing; Tutorials; Reinforcement learning; Network security; Resilience; Substrates; Ad hoc vehicular networks; ATTACK;
D O I
10.1109/MWC.001.2100282
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The arrival of the 5G era brings unprecedented opportunities and challenges to vehicular networks. As one of the most innovative and important technologies of 5G, network slicing can separate the physical substrate network into multiple logical networks, and meet the requirements of various vehicle services simultaneously. Therefore, its superiority in vehicular networks has attracted extensive attention. However, with the gradual transition of 5G and beyond vehicular networking (5G/B5G-VN) from theory to practice, little attention has been paid to the security of network slicing. Without security guarantee, it is difficult for network slicing to be formally put into use and widely accepted. In view of this, we propose a tutorial on the network slicing security for 5G/B5G-VN, aiming to present the potential of network slicing for security protection and also analyze its security threats from multiple perspectives. In addition, a case study of using deep reinforcement learning for recovery after attacks is provided to improve the service success rate of slices and imbue 5G/B5G-VN with a certain degree of resilience.
引用
收藏
页码:126 / 133
页数:8
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