Common use of Problem and challenges Clause in Contracts

Problem and challenges. Pervasive Vehicle-to-everything (V2X) connectivity and the emergence of effective data-driven methods based on AI/ML drive a paradigm shift towards Connected and Automated Mobility (CAM) services and applications [18]. A key functionality in vehicular systems that can benefit from AI/ML is security, which is essential for ensuring road safety in CAM environments. V2X security threats and attacks can either originate from malicious outsiders which are vehicles/users exogenous to the original system, or insiders which are already authenticated and possess valid credentials to interact with other legitimate entities in the system. While outsider attacks can be efficiently addressed even in highly dense V2X scenarios with a proper extension of the 5G Authentication and Key Agreement (5G-AKA) procedure, as shown in [19], insider attacks are often difficult to detect and contain, particularly when attackers behave intelligently while conforming to normal system behaviour. For example, an already authenticated vehicle may be able to intentionally transmit false kinematic information (e.g., position, speed, acceleration, heading-angle data) in its broadcast messages and cause disruption in the network. Seemingly abnormal vehicular activity originated from malicious actors (e.g., vehicles) may take the form of highly sophisticated attacks. Such malicious/selfish behaviours from such rogue insiders are commonly referred to as misbehaviours in V2X, and they pose a serious threat when transmitting erroneous/incorrect data in safety-critical situations. Ensuring the semantic correctness of exchanged V2X information is thus of paramount importance.