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Securing Cloud-Assisted Connected and Autonomous Vehicles: An In-Depth Threat Analysis and Risk Assessment.

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  • 1Warwick Manufacturing Group (WMG), University of Warwick, Coventry CV4 7AL, UK.

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Summary
This summary is machine-generated.

This study enhances threat analysis and risk assessment (TARA) for Cloud-Assisted Connected and Autonomous Vehicles (CCAVs). It refines TARA methods to better identify vulnerabilities and manage risks in complex CCAV systems.

Keywords:
attack treeautonomous vehiclescloudconnected vehiclescountermeasurescyber securityedge computingrisk assessmenttaxonomythreat analysisthreat modeling

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Area of Science:

  • Cybersecurity
  • Automotive Engineering
  • Risk Management

Background:

  • Cloud-Assisted Connected and Autonomous Vehicles (CCAVs) face increasing cyberattack risks due to evolving threats and complex systems.
  • Existing Threat Analysis and Risk Assessment (TARA) methodologies often fall short in capturing CCAV-specific threat data, leading to reduced effectiveness.
  • Factors like intricate hardware-software interactions, rapid technological change, and diverse standards complicate CCAV security.

Purpose of the Study:

  • To systematically evaluate and enhance TARA methodologies for CCAVs.
  • To improve the precision in identifying vulnerabilities, quantifying risks, and defining threat boundaries in CCAV systems.
  • To develop a novel defense taxonomy and inform advanced threat analysis for enhanced security engineering.

Main Methods:

  • Systematic evaluation of existing TARA methods.
  • Application of the Spoofing, Tampering, Repudiation, Information disclosure, Denial of service, and Elevation of privileges (STRIDE) threat model.
  • Utilized Damage, Reproducibility, Exploitability, Affected Users, and Discoverability (DREAD) for risk assessment.
  • Development of an attack tree and a novel defense taxonomy.

Main Results:

  • Identified specific vulnerabilities and quantified associated risks within CCAV architectures.
  • Demonstrated the enhanced efficacy of the refined TARA in capturing security requirements, threats, and limits with greater precision.
  • Provided a structured approach to understanding and mitigating multi-staged attacks against hardware-software assets.

Conclusions:

  • The proposed TARA enhancements offer a more precise and effective approach to cybersecurity for CCAVs.
  • Addressing complex interactions and emerging vulnerabilities is crucial for robust CCAV security.
  • This research provides a foundation for advanced threat analysis and risk management in cyberphysical CCAV systems.