Strategic Utilization of Digital Twins for examining elastic attack surfaces and replicating attack scenarios for Vulnerability analysis on road vehicle components

With the advent of trending software-centric architecture for vehicles, the complexity of judging the vehicle's software behavior increases the exploitation of missed, overlooked, or untreated vulnerabilities. More and more often, automotive products are targeted for many malicious reasons. Automotive security incident management does include continuous monitoring of incidents and vulnerabilities, but it poses challenges in reproducing those attacks and revalidating the security goals. It lacks visualization of the attack scenarios, attack vectors, and knowledge required to replicate and reproduce the attack. If the visualization of the vulnerable path is traceable, then attack scenarios, attack vectors, and the knowledge required to demonstrate the attack for vulnerability assessment can be achievable with fixed timelines. Architecture that supports digital twins to promote vulnerability assessment is most appreciative. The vision of this paper is to provide a theoretical approach to visualization with cyber-digital twins to accurately rate the safety impact of failure and vulnerability analysis. Enhancing the assessment of vulnerabilities on elastic surfaces. The derivation of residual risk and its documentation consider business impact factors, lastly, needed components, and the analysis results of our novel approach to promote replication of attack scenarios over time and effort using digital twins.