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Machine Learning for Driver Detection through CAN bus

机译:通过CAN总线进行驾驶员检测的机器学习

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In last years vehicular network safety and security are attracting interest from both industries and researchers. In this paper, starting from a set of features gathered from the in-vehicle CAN bus, we show how machine learning algorithms can be useful to discriminate between the car owner and impostors. Furthermore, we assess several machine learning classifiers ability to predict instances not evaluated in the training set.
机译:近年来,车载网络的安全性越来越受到行业和研究人员的关注。在本文中,我们将从车载CAN总线收集的一组功能入手,展示如何使用机器学习算法来区分车主和冒名顶替者。此外,我们评估了几种机器学习分类器的能力,以预测训练集中未评估的实例。

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