A lightweight intrusion detection system for connected autonomous vehicles based on ECANet and image encoding

This publication has 26 references indexed in Scilit:

• GDT-IDS: graph-based decision tree intrusion detection system for controller area network
  The Journal of Supercomputing, 2025
• Cost-Sensitive Detection of DoS Attacks in Automotive Cybersecurity Using Artificial Neural Networks and CatBoost
  Journal of Network and Systems Management, 2025
• An anomaly detection model for in-vehicle networks based on lightweight convolution with spectral residuals
  Computers & Security, 2025
• Supervised contrastive ResNet and transfer learning for the in-vehicle intrusion detection system
  Expert Systems with Applications, 2023
• A survey of deep learning-based intrusion detection in automotive applications
  Expert Systems with Applications, 2023
• A deep learning-based intrusion detection system for in-vehicle networks
  Computers and Electrical Engineering, 2022
• Security on in-vehicle communication protocols: Issues, challenges, and future research directions
  Computer Communications, 2021
• A location privacy protection scheme for convoy driving in autonomous driving era
  Peer-to-Peer Networking and Applications, 2021
• CAN-ADF: The controller area network attack detection framework
  Computers & Security, 2020
• An Intelligent Secured Framework for Cyberattack Detection in Electric Vehicles’ CAN Bus Using Machine Learning
  IEEE Access, 2019