Fei Li1, *, Jiayan Zhang1, Edward Szczerbicki2, Jiaqi Song1, Ruxiang Li 1, Renhong Diao1
CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 653-681, 2020, DOI:10.32604/cmc.2020.011264
Abstract The increasing use of the Internet with vehicles has made travel more
convenient. However, hackers can attack intelligent vehicles through various technical
loopholes, resulting in a range of security issues. Due to these security issues, the safety
protection technology of the in-vehicle system has become a focus of research. Using the
advanced autoencoder network and recurrent neural network in deep learning, we
investigated the intrusion detection system based on the in-vehicle system. We combined
two algorithms to realize the efficient learning of the vehicle’s boundary behavior and the
detection of intrusive behavior. In order to verify the accuracy and efficiency… More >
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