{
  "$schema": "https://resources.data.gov/schemas/dcat-us/v1.1/schema/catalog.json",
  "conformsTo": "https://project-open-data.cio.gov/v1.1/schema",
  "@type": "dcat:Catalog",
  "@context": "https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld",
  "dataset": [
    {
      "@type": "dcat:Dataset",
      "accessLevel": "public",
      "bureauCode": null,
      "contactPoint": {
        "fn": "NTL Digital Submissions",
        "hasEmail": "mailto:NTLDigitalSubmissions@dot.gov",
        "@type": "vcard:Contact"
      },
      "dataQuality": true,
      "description": "The purpose of this project is to create a high-fidelity simulation platform to assess 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.",
      "distribution": [],
      "format": "ZIP",
      "issued": "2025-06-01",
      "keyword": [
        "Autonomous vehicles",
        "Computer security"
      ],
      "language": [
        "en"
      ],
      "license": "https://creativecommons.org/licenses/by/4.0/",
      "modified": "2026-08-28",
      "policyStatement": "This dataset was made public under the requirements enumerated in the U.S. Department of Transportation's 'Plan to Increase Public Access to the Results of Federally-Funded Scientific Research' Version 1.1 <https://doi.org/10.21949/1520559> and guidelines suggested by the DOT Public Access website <https://doi.org/10.21949/1503647>, in effect and current as of December 03, 2020.",
      "programCode": null,
      "publisher": {
        "@type": "org:Organization",
        "name": "National Center for Transportation Cybersecurity and Resiliency (TraCR) National University Transportation Center"
      },
      "references": null,
      "spatial": "United States",
      "title": "\tCybersecurity Testbed for Connected and Autonomous Vehicles (CAVs) [supporting dataset]",
      "webService": "https://rosap.ntl.bts.gov/fedora/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:dot.stacks:"
    }
  ]
}