Cybersecurity Testbed for Connected and Autonomous Vehicles (CAVs) [supporting dataset]

Details

• Creators:
  Ukkusuri, Satish V. ; Cardenas, Alvaro ; Fremont, Daniel J. ; Chowdhury, Mashrur "Ronnie" ; Salek, M. Sabbir ; Comert, Gurcan ; Jeihani, Mansoureh
• Corporate Creators:
  National Center for Transportation Cybersecurity and Resiliency (TraCR) National University Transportation Center (UTC)
• Corporate Contributors:
  United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
• Subject/TRT Terms:
  • Connected vehicles
  • Autonomous vehicles
  • Computer security
  • Transportation safety
  • Vehicle to everything communications
  • Cyberattacks
  • Test beds
  • Global Positioning System
  • Infrastructure
  • Data
  More +
• Resource Type:
  Dataset
• Right Statement:
  Open Access; https://creativecommons.org/licenses/by/4.0/
• Geographical Coverage:
  United States
• Corporate Publisher:
  National Center for Transportation Cybersecurity and Resiliency (TraCR) National University Transportation Center (UTC)
• Abstract:
  The purpose of this project is to create a high-fidelity simulation platform to assess s the cascading impacts of cyberattacks on connected and autonomous vehicle (CAV) systems. As cities increasingly adopt autonomous and connected technologies to enhance transportation efficiency and safety, they also expose critical infrastructure to new cyber-physical threats. While past studies have demonstrated vulnerabilities such as GPS spoofing and traffic signal manipulation, most are limited to small-scale scenarios and fail to capture system-wide consequences. We develop an open-source framework that supports scalable data generation, anomaly detection, and the simulation of complex attack scenarios across vehicle and network levels. Built on a co-simulation architecture, the platform integrates V2X communication, vehicle dynamics, and traffic flow models, and incorporates fleet control to evaluate operational disruptions. It also simulates basic safety message (BSM) attacks to reveal how compromised communications can trigger unsafe behaviors and traffic instabilities. By facilitating the study of realistic, largescale threat scenarios and their cascading effects, this project lays a critical foundation for advancing transportation cybersecurity research and promotes the development of more resilient and secure mobility systems. ; The total size of the ZIP file is 24,479 KB.
• Content Notes:
  This dataset additional data and software in a GitHub repository. This repository is accessible online: https://github.com/umnilab/METS-R_HPC/tree/master/data
• Format:
  ZIP
• Funding:
  69A3552344812 ; 69A3552348317
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/93217/dot_93217_DS1.json
• File Type:
  [JSON - 3.10 KB]
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha-512:0e3eb5d938a089e0f741addfcf5e1426c45326c027e2bc91c9e0f40fcde4d452cdd2386663a8065f2654f918bf5348d0f201efdf2930c2140e229839d27e18e6