Machine Learning for Intrusion Detection in Vehicular Ad-hoc Networks (VANETs): A Survey-Reference-Cited by-同舟云学术

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Machine Learning for Intrusion Detection in Vehicular Ad-hoc Networks (VANETs): A Survey

Published:2024-08-06 Issue: Volume: Page:1-10
ISSN:
Container-title:2024 4th International Conference on Emerging Smart Technologies and Applications (eSmarTA)
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Author:

Al-Khulaidi Nesmah A.¹,Zahary Ammar T.²,Al-Shargabi Asma A.³,Hazaa Muneer A. S⁴

Affiliation:

1. Yemen Academy for Graduate Studies,Department of Computer Networks,Sana'a,Yemen

2. Faculty of Computing and IT University of Science and Technology,Department of Computer Science,Sana'a,Yemen

3. College of Computer, Qassim University,Department of Information Technology,Buraydah,Saudi Arabia,51452

4. Faculty of Computer and Information System Thamar University,Department of Computer Science,Thamar,Yemen

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10638789/10638835/10639016.pdf?arnumber=10639016

Reference54 articles.

1. Machine Learning Techniques to Detect DDoS Attacks on VANET System: A Survey

2. Recent Advances in Machine-Learning Driven Intrusion Detection in Transportation: Survey

3. A comparative study of Machine learning algorithms for VANET networks

4. Comparative Analysis of Various Approaches for DoS Attack Detection in VANETs

5. Intrusion Detection in VANETs and ACVs using Deep Learning

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