区块链与人工智能的融合对自动驾驶汽车恶意行为进行分类

Dhairya Jadav, M. Obaidat, S. Tanwar, Rajesh Gupta, K. Hsiao
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引用次数: 3

摘要

区块链是一种流行的技术,其应用旨在实现安全性、隐私性、可追溯性和信任。其中一个应用就是自动驾驶汽车(AVs)。无人驾驶汽车最大的问题是其安全性。恶意AV可能会导致危及生命的事故。我们提出了一个基于区块链和集成学习的系统,将车辆分类为恶意车辆,以解决上述安全问题。自动驾驶汽车交易验证的智能合约被设计用于计算任何自动驾驶汽车执行的恶意活动的数量。最后,结果表明,所提出的模型达到了本文的目标,准确率为97.5%。
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Amalgamation of Blockchain and AI to Classify Malicious Behavior of Autonomous Vehicles
Blockchain is a prevalent technology whose applications are aimed towards security, privacy, traceability and trust. One such application is autonomous vehicles (AVs). The biggest concern of AVs is their safety. A malicious AV can cause accidents that may be life-threatening. We have proposed a blockchain and ensemble learning-based system to classify the vehicles as malicious to address the aforementioned safety issue. Smart contracts for AVs transaction verification have been designed to count the number of malicious activities performed by any AV. Finally, results show that the proposed model achieved the goal of this paper with an accuracy of 97.5 %.
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