Connected Vehicles Security: A Lightweight Machine Learning Model to Detect VANET Attacks
Vehicular ad hoc networks (VANETs) aim to manage traffic, prevent accidents, and regulate various parts of traffic. However, owing to their nature, the security of VANETs remains a significant concern. This study provides insightful information regarding VANET vulnerabilities and attacks. It investi...
Saved in:
| Main Authors: | Muawia A. Elsadig, Abdelrahman Altigani, Yasir Mohamed, Abdul Hakim Mohamed, Akbar Kannan, Mohamed Bashir, Mousab A. E. Adiel |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
|
| Series: | World Electric Vehicle Journal |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2032-6653/16/6/324 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A lightweight certificateless aggregate signature scheme without pairing for VANETs
by: Qiuling Yue, et al.
Published: (2025-07-01) -
SDN-Based VANET Routing: A Comprehensive Survey on Architectures, Protocols, Analysis, and Future Challenges
by: Nehad Hameed Hussein, et al.
Published: (2025-01-01) -
Review of Certificateless Authentication Scheme for Vehicular Ad Hoc Networks
by: Abdulaziz Zaid A. Aljarwan, et al.
Published: (2025-01-01) -
A Systematic Literature Review on Privacy Preservation in VANETs: Trends, Challenges, and Future Directions
by: Esti Rahmawati Agustina, et al.
Published: (2025-01-01) -
Integrated VLC/RF With Adaptive Power Control for Reliable Cluster-Based VANET Communications
by: Ahmed M. El-Eraki, et al.
Published: (2025-01-01)