Connected Vehicle Cybersecurity Platform Using Digital Twin Attack Graphs
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The automotive industry faces challenges in efficiently monitoring and managing the cybersecurity posture of connected vehicles, due to the complexity of internal systems and multiple connectivity channels, which creates a multitude of attack surfaces for malicious users. Current methods rely on manual testing and audits, making it costly and impractical to identify and remediate vulnerabilities in a timely manner.
Innovation Solution
A connected vehicle cybersecurity platform that leverages digital twins across multiple layers of the connected vehicle ecosystem, generating analytical attack graphs (AAGs) based on digital twins to evaluate vulnerabilities and remedies within the ecosystem. This platform simulates and evaluates the connected vehicle ecosystem using AAGs, representing potential lateral movement, and selectively adjusts remedial measures to mitigate risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual testing and audits are used to identify vulnerabilities in each in-vehicle component, then security assessment can be performed, but the cost in terms of time, money, and technical resources becomes extremely expensive and impractical
Solution Approach 1:
The patent creates a digital twin (virtual copy) of the connected vehicle system that replicates the complex network of in-vehicle components, connectivity channels, and attack surfaces. This digital replica enables automated security assessment without requiring expensive manual testing of each physical component, thereby maintaining security assessment capability while dramatically reducing time, money, and technical resource costs.
2Measurement precision
If manual testing is performed on each in-vehicle component individually, then vulnerabilities can be identified, but the process cannot keep up with vulnerabilities arising from frequent changes and software updates
Solution Approach 1:
The digital twin platform enables continuous, automated security assessment that runs ongoing simulations and analyses as the vehicle system evolves. Unlike discrete manual testing, the system continuously monitors and re-evaluates the digital replica whenever changes occur in the connected vehicle ecosystem, ensuring vulnerability identification keeps pace with frequent software updates and new threats without time loss.
Solution Approach 2:
The system performs preliminary security assessments on the digital twin before changes are deployed to the actual vehicle system. By simulating and evaluating security implications in advance on the virtual replica, potential vulnerabilities from upcoming software updates or configuration changes can be identified and addressed before they affect the real system, preventing rather than just detecting issues.
3Reliability
If comprehensive security monitoring is implemented across multiple connectivity channels (C2C, V2V, V2X, V2N), then security posture can be managed, but the complexity of the system increases significantly
Solution Approach 1:
The digital twin acts as an intermediary that consolidates and simplifies the monitoring of multiple connectivity channels. Instead of directly managing the complexity of C2C, V2V, V2X, and V2N communications, the system creates a virtual model that represents all these channels and their interactions in a unified, manageable structure. This intermediary layer enables comprehensive security posture monitoring while abstracting away the underlying system complexity.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Implementations include determining a set of components within the connected vehicle ecosystem, components within the set of components representing at least one layer within the connected vehicle ecosystem, for each component in the set of components: providing a set of facts representative of the respective component, and providing a component digital twin using the set of facts, defining a set of digital twins including digital twins of components in the set of components, generating, using the set of digital twins, at least one AAG representative of potential lateral movement between components of the at least one layer within the connected vehicle ecosystem, the at least one AAG representing a contextual digital twin of components operating within the connected vehicle ecosystem, and evaluating the connected vehicle ecosystem using the at least one AAG.