A Reputation System Using a Bayesian Statistical Filter in Vehicular Networks
A Reputation System Using a Bayesian Statistical Filter in Vehicular Networks
复制标题
在车辆网络中使用贝叶斯统计过滤器的声誉系统
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
L. Khoukhi
中科院分区：
文献类型：
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作者：
Y. Begriche;Rida Khatoun;A. Rachini;L. Khoukhi
无线技术的快速发展导致了具有集中式和分散式架构的新型高动态网络的出现。车载网络（VANETs）技术就是其中之一。车辆之间的通信将通过向车辆驾驶员提供有关交通和道路状况的信息，从而提高道路的效率和安全性。为了保护车辆乘客和驾驶员，这些网络需要一个安全的基础设施来防止恶意行为的发生。本文提出了一种基于贝叶斯统计过滤器的强信誉系统，用于检测vanet中选择性或完全丢弃数据包的恶意节点。提出的方法允许车辆相互作用以检测恶意车辆，给它一个坏名声并将其从网络中排除。
The rapid development of wireless technologies has led to the emergence of new types of highly dynamic networks with centralized and decentralized architectures. Vehicular networks (VANETs) technology is one of those networks. The communication between vehicles will lead to more efficient and secured roads by providing information about traffic and road conditions to vehicle drivers. In order to protect vehicle passengers and drivers, these networks need a secure infrastructure to prevent malicious behavior from happening. This paper proposes a strong reputation system based on a Bayesian statistical filter to detect malicious nodes which drop packets selectively or completely in VANETs. The proposed approach allows vehicles to interact in order to detect the malicious one, give it a bad reputation and exclude it from the network.