Strategic Utilization of Digital Twins for Examining Elastic Attack Surfaces and Replicating Attack Scenarios for Vulnerability Analysis on Road Vehicle Components

As vehicles adopt software-centric architectures, assessing vehicle software behavior becomes more complex, which can lead to the exploitation of overlooked or untreated vulnerabilities. Using these backdoors, attacks frequently targeted automotive products for malicious reasons. Automotive security incident management involves continuous monitoring of incidents and vulnerabilities. However, it faces challenges in reproducing attacks and revalidating security goals. The lack of visualization of attack scenarios, and vectors, and the knowledge required to replicate attacks hinders vulnerability assessment. The proposed approach aims to improve vulnerability assessment and document residual risks. It promotes replicating attack scenarios using cyber digital twins to support threat modeling, risk assessment, and threat analysis. The research paper focuses on utilizing digital twins for cybersecurity incident response, threat monitoring, and vulnerability exploitation by examining elastic attack surfaces and promoting threat Intelligence.