Researchers have developed an artificial intelligence tool to safeguard vehicles from cyber threats, addressing a major challenge in the Internet of Vehicles (IoV) ecosystem. The IoV refers to a network where vehicles communicate with each other and intelligent devices in parking lots, pedestrians, and road infrastructure. However, the security of these vehicles is vulnerable to cyberattacks that can cause catastrophic events. Scientists from the University of Sharjah, the University of Maryland, and Abdul Wali Khan University Mardan have proposed an ML-based authentication scheme that trains and classifies vehicles at edge servers in a distributed manner, preserving privacy and minimizing bandwidth consumption and delay. The scheme uses machine learning algorithms to analyze and verify communication patterns in real-time, strengthening security against common cyber-attacks. The researchers' approach extends the decision power of vehicles and edge servers to identify adversaries, ensuring faster and more efficient communication.
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