RT Journal Article
SR Electronic
A1 Mohammed, Ibraheem Hatem
T1 Internet of Vehicles Security Improvement Based Controller Area Network and Artificial Intelligence
JF Communications - Scientific Letters of the University of Zilina
YR 2025
VO 27
IS 2
SP C14
OP C23
DO 10.26552/com.C.2025.017
UL https://komunikacie.uniza.sk/artkey/csl-202502-0002.php
AB The Internet of Vehicle (IoV) is revolutionizing the automobile sector by allowing vehicles to interact between them and with roadside infrastructure. The Controller Area Network (CAN) is a vital component of such Autonomous vehicles (AVs), allowing communication between various Electronic Control Units (ECUs). However, the CAN protocol's intrinsic lack of security renders it opens to a variety of cyber-attacks, posing substantial hazards to both safety and privacy. This research proposes a defence mechanism for the real-time threat detection. It investigates the use of deep learning with multi-layer perceptron to improve the security of CAN networks inside the IoV framework. The suggested method is highly effective in identifying and mitigating potential risks, as evidenced by extensive testing on real-world CAN datasets.