Deep Learning-based Embedded Intrusion Detection System for Automotive CAN

Author:

Khandelwal Shashwat1,Wadhwa Eashan1,Shreejith Shanker1

Affiliation:

1. Trinity College Dublin,Department of Electronic and Electrical Engineering,Dublin,Ireland

Funder

NVIDIA

Publisher

IEEE

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. IoT based Real Time Anomaly Detection in Automotive ECUs Using Machine Learning;2024 International Conference on Recent Advances in Electrical, Electronics, Ubiquitous Communication, and Computational Intelligence (RAEEUCCI);2024-04-17

2. Comparative Evaluation of Machine Learning-Based Controller Area Network Intrusion Detection Systems;2023 14th International Conference on Information and Communication Systems (ICICS);2023-11-21

3. In-vehicle network intrusion detection systems: a systematic survey of deep learning-based approaches;PeerJ Computer Science;2023-10-26

4. Exploring Highly Quantised Neural Networks for Intrusion Detection in Automotive CAN;2023 33rd International Conference on Field-Programmable Logic and Applications (FPL);2023-09-04

5. Quantised Neural Network Accelerators for Low-Power IDS in Automotive Networks;2023 Design, Automation & Test in Europe Conference & Exhibition (DATE);2023-04

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