Name
Abstract | ||
|---|---|---|
The development of the Internet of Vehicles (IoV) has made people’s lives and travels safer, more efficient, and more comfortable. The combination of edge computing and IoV can provide processing and storage capabilities close to vehicles, thus becoming a potential paradigm. At this time, the software-defined networking (SDN) architecture is extremely necessary to realize centralized control and convenient management for complex and dynamic vehicular edge networks. However, as the brain of the SDN architecture, little attention has been paid to the security of the SDN controller. Once the controller is threatened, severe global chaos may happen. Therefore, in this article, we study the attack against the SDN controller, which is the topology poisoning attack. We successfully implement this attack in four mainstream controllers and analyze its impact from multiple levels. To the best of our knowledge, we are the first to study this attack in the vehicular edge network. In addition, in view of the counter-attacks of the existing defence mechanisms, we propose an attack-tolerance scheme based on deep reinforcement learning (DRL) to enhance the vehicular edge network with a certain degree of self-recovery. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/JIOT.2020.2984088 | IEEE Internet of Things Journal |
Keywords | DocType | Volume |
Network topology,Topology,Security,Computer architecture,Relays,Servers,Edge computing | Journal | 7 |
Issue | ISSN | Citations |
10 | 2327-4662 | 2 |
PageRank | References | Authors |
0.36 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiadai Wang | 1 | 72 | 3.38 |
| Yawen Tan | 2 | 9 | 1.79 |
| Jiajia Liu | 3 | 140 | 11.42 |
| Yanning Zhang | 4 | 1613 | 176.32 |