NATWORK

Autonomous vehicles (AVs) rely heavily on 6G networks to communicate with other vehicles, infrastructure, and the cloud. However, the wireless links used by AVs are susceptible to various types of interference and jamming attacks, which can compromise the safety and reliability of the vehicle. Machine learning and AI can detect, classify, and mitigate jamming attacks in real time by analysing signal patterns, adapting to changing signal environments and identifying anomalous behaviour. By leveraging the power of 6G networks and cutting-edge machine learning techniques, AVs can be guaranteed a safer and more reliable future.

AVs will rely heavily on 6G networks for communication and coordination, making them vulnerable to jamming attacks that can disrupt communication and pose significant safety risks. This use case explores how advanced anti-jamming technologies that ensure reliable and secure communication for AV networks can enable safer and more efficient transportation systems.