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Intelligent vehicles require dynamic security. This study introduces a hierarchical self-aware security architecture for system-level accountability in connected vehicles, enhancing real-time threat response.

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Area of Science:

  • Cybersecurity
  • Intelligent Transportation Systems
  • Automotive Engineering

Background:

  • Intelligent vehicles face escalating security risks due to increasing connectivity and data exchange.
  • The evolution towards vehicles-to-everything (V2X) communication amplifies security complexities, demanding adaptive solutions.
  • Current static security measures are insufficient for the dynamic nature of intelligent vehicle environments.

Purpose of the Study:

  • To propose a novel hierarchical self-aware security architecture for intelligent vehicles.
  • To establish system-level accountability within the vehicle's security framework.
  • To demonstrate the relevance and efficacy of this architecture for future mobility.

Main Methods:

  • Development of a hierarchical security architecture emphasizing self-awareness and accountability.
  • Integration of algorithms for real-time monitoring, analysis, and decision-making across security layers.
  • Implementation of a security-specific in-vehicle black box with external virtual security operation center (VSOC) integration.

Main Results:

  • The proposed architecture enables system-level accountability, moving beyond static security approaches.
  • Hierarchical layers facilitate real-time security operations, including monitoring and analysis.
  • Integration with a VSOC enhances remote security management and response capabilities.

Conclusions:

  • The hierarchical self-aware security architecture provides a robust, adaptive solution for intelligent vehicle security.
  • System-level accountability is crucial for managing the complexities of connected and autonomous vehicles.
  • This approach enhances real-time security decision-making and integrates in-vehicle and external security operations effectively.