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Security Enhancing Method in Vehicular Networks by Exploiting the Accurate Traffic Flow Prediction

机译:通过利用精确的交通流量预测,在车辆网络中的安全增强方法

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In recent years, to improve the transportation system’s efficiency, relying on the development of vehicular wireless communication technology and corresponding in-vehicle sensor technology, intelligent transportation systems have become the focus of attention in academia and industry. This is because, by improving the vehicle’s ability to perceive the surrounding traffic environment through the exchange of information between vehicles, the vehicle’s safety can be effectively improved, which reduces the occurrence of traffic accidents, in turn improving the efficiency of the transportation system. However, while data exchange brings convenience, similar to the other data communication applications, communication security issues inevitably enter the Internet-of-Vehicles environment since the vehicle is no longer an isolated individual. Accordingly, in this paper, we will propose a data transmission security improvement method based on accurate traffic flow prediction for addressing a specific data theft problem. Briefly, our method can detect the fraud vehicle that spread fake traffic information to increase the possibility that it may be selected as a relay node, thereby increasing its theft of the data of related users who use it as a relay node. Intensive simulation experiments are conducted to evaluate and prove the efficiency of our proposed work.
机译:近年来,为了提高运输系统的效率,依靠车辆无线通信技术的发展和相应的车载传感器技术,智能交通系统已成为学术界和工业中关注的重点。这是因为,通过改善车辆通过车辆之间的信息交流来感知周围交通环境的能力,可以有效地改善了车辆的安全性,这减少了交通事故的发生,从而提高了运输系统的效率。然而,虽然数据交换带来便利性,类似于其他数据通信应用,但是由于车辆不再是隔离的个体,通信安全问题不可避免地进入车辆互联网环境。因此,在本文中,我们将基于用于解决特定数据盗窃问题的准确交通流量预测的数据传输安全改进方法。简而言之,我们的方法可以检测扩展虚假交通信息的欺诈车辆,以增加它可以选择作为中继节点的可能性,从而增加其与将其作为中继节点的相关用户的数据被盗。进行了密集的仿真实验,以评估和证明我们拟议的工作的效率。

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