… effective intrusion detection system (IDS). This work develops an IDS for in-vehicle networks
… using deep learning. The IDS-IVN uses convolutional neural and long–short-term memory …

… in-vehicle network. In this work, we proposed a hybrid deep learning-based intrusion detection
system … in-vehicle network traffic accurately. For this purpose, we use convolutional neural …

… In this article, a deep learning-based intrusion detection system is presented for the IoV. The
sys… might be extended for other deep learning architectures to enhance in-vehicle intrusion …

… analysis of the detection capability for the unknown … intrusion detection models. Therefore,
this paper investigates ten representative advanced deep-learning-based intrusion detection …

… The idea of machine learning-based IDS deployed to the CAN bus … , this study addresses
a diverse range of threat classification problems in intrusion detection systems using the …

… Embedding a deep learning-based clustering approach in the second stage of the
algorithm will also boost the performance in all the experiments conducted. The clustering loss …

… This paper presents a novel machine learning based intrusion detection system for CAN
bus network that effectively detects the intrusions and attacks made on the AVs. It disseminates …

… In this work, a deep transfer learning-based LeCun Network (LeNet) model has been
proposed for effective intrusion detection in-vehicle network CAN bus protocol. The proposed …

… an intrusion detection system (IDS) based on a deep convolutional neural … machine
learning-based anomaly detectors to classify the anomalies. Similarly, network intrusion detection …

… In this paper, a holistic, comprehensive, Machine Learning-Based intrusion detection system
for the CAN bus is proposed to secure the critical in-vehicle network. The proposed system …