Cybersecurity in Autonomous and Connected Vehicles: A Systems-Level Threat Analysis and Resilience Framework

Abstract

The rapid evolution of autonomous and connected vehicles has ushered in transformative changes in mobility, enabling real-time data exchange, cooperative driving, and over-the-air feature enhancements. However, this connectivity also exposes vehicles to a vast and complex cyber threat landscape. This article examines the cybersecurity risks inherent in autonomous and connected vehicles, including attacks on vehicle-to-everything communications, electronic control units, sensor spoofing, and remote code execution. It proposes a layered cybersecurity resilience framework based on threat modeling, intrusion detection, and cryptographic security protocols tailored for automotive architectures. The article also addresses implementation challenges related to legacy systems, resource constraints, supply chain complexity, and regulatory fragmentation. The framework offers adaptive, standards-aligned methodologies for threat prevention, detection, and mitigation in next-generation intelligent transport systems, contributing practical defense strategies for securing autonomous vehicle platforms against evolving threats.