An Intelligent Edge-Chain-Enabled Access Control Mechanism for IoV
- 23 February 2021
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Internet of Things Journal
- Vol. 8 (15), 12231-12241
- https://doi.org/10.1109/jiot.2021.3061467
Abstract
The current security method of Internet-of-Vehicles (IoV) systems is rare, which makes it vulnerable to various attacks. The malicious and unauthorized nodes can easily invade the IoV systems to destroy the integrity, availability, and confidentiality of information resources shared among vehicles. Indeed, access control mechanism can remedy this. However, as a static method, it cannot timely response to these attacks. To solve this problem, we propose an intelligent edge-chain-enabled access control framework with vehicle nodes and roadside units (RSUs) in this study. In our scenario, vehicle nodes act as lightweight nodes, whereas RUSs serve as full and edge nodes to provide access control services. Considering the low accuracy of risk prediction due to limited training sets, we leverage a generative adversarial networks (GANs) to convert the risk prediction to a sequence generation. Moreover, aiming at the problems of gradient disappearance and mode collapse existed in the original GANs, we devise a Wasserstein combined GANs (WCGANs). Simulation results demonstrate that WCGAN has higher prediction accuracy than the original GANs. Additionally, it can also improve the accuracy of access control of risk prediction-based access control (RPBAC) model.Funding Information
- Open Fund of the Ministry of Education Key Laboratory of Networks Security and Intelligent Technology, Beijing University of Posts and Telecommunications
- General Program of Natural Science Foundation of Chongqing (cstc2020jcyj-msxmX1021)
- Science and Technology Research Program of Chongqing Municipal Education Commission (KJZD-K202000602)
- National Science Fundation of China (62001423)
- Henan Provincial Key Research, Development and Promotion Project (212102210175)
- Henan Provincial Key Scientific Research Project for College and University (21A510011)
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