通过物联网设备和传感器实现车辆之间通信的区块链框架

J. S. Raj
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引用次数: 3

摘要

在今天的情况下,自动驾驶汽车的出现确实是一个潜在的研究领域。在过去十年中,互联汽车(CV)受到了广泛关注,从而产生了汽车即服务(CVaaS)。随着出租车服务的出现,连接到车辆网络的车辆之间需要可靠、无缝和安全的信息传输。因此,车联网的概念转变为自主和互联汽车的新概念。这些自动驾驶汽车将通过减少拥堵,提供来自车辆的即时信息,从而提供更好的体验。自动驾驶汽车发明面临的一个重大缺点是入侵者的恶意攻击,他们往往会误导车辆之间的通信,导致智能设备受损。为了解决这些问题,实时保护和保护自动驾驶汽车控制系统的最佳方法是区块链。这项研究工作提出了一个区块链框架,以解决自动驾驶汽车的安全挑战。本研究提高了智能车辆的安全性,从而防止入侵者进入车辆网络。为了验证建议的技术,采用了诸如更改存储的用户评级、概率身份验证场景、智能设备泄露和虚假用户请求等货币安全标准。观察到的结果已被记录和分析,显示出82%的成功率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Blockchain Framework for Communication between Vehicle through IoT Devices and Sensors
The advent of autonomous vehicles is indeed a potential field of research in today's situation. Connected Vehicles (CV) have received a lot of attention in the last decade, which has resulted in CV as a Service (CVaaS). With the advent of taxi services, there is a need for or demand for robust, seamless, and secure information transmission between the vehicles connected to a vehicular network. Thus, the concept of vehicular networking is transformed into novel concept of autonomous and connected vehicles. These autonomous vehicles will serve as a better experience by providing instant information from the vehicles via congestion reduction. The significant drawback faced by the invention of autonomous vehicles is the malicious floor of intruders, who tend to mislead the communication between the vehicles resulting in the compromised smart devices. To address these concerns, the best methodology that will protect and secure the control system of the autonomous vehicle in real time is blockchain. This research work proposes a blockchain framework in order to address the security challenges in autonomous vehicles. This research work enhances the security of smart vehicles thereby preventing intruders from accessing the vehicular network. To validate the suggested technique, money security criteria such as changing stored user ratings, probabilistic authentication scenarios, smart device compromise, and bogus user requests were employed. The observed findings have been documented and analysed, revealing an 82% success rate.
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