Risk Assessment and Threat Modeling for safe autonomous driving technology
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866918008869355520 |
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| author | Paz, Ian Alexis Wong Balan, Anuvinda Campos, Sebastian Orenstain, Ehud Dhakal, Sudip |
| author_facet | Paz, Ian Alexis Wong Balan, Anuvinda Campos, Sebastian Orenstain, Ehud Dhakal, Sudip |
| contents | This research paper delves into the field of autonomous vehicle technology, examining the vulnerabilities inherent in each component of these transformative vehicles. Autonomous vehicles (AVs) are revolutionizing transportation by seamlessly integrating advanced functionalities such as sensing, perception, planning, decision-making, and control. However, their reliance on interconnected systems and external communication interfaces renders them susceptible to cybersecurity threats.
This research endeavors to develop a comprehensive threat model for AV systems, employing OWASP Threat Dragon and the STRIDE framework. This model categorizes threats into Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service (DoS), and Elevation of Privilege.
A systematic risk assessment is conducted to evaluate vulnerabilities across various AV components, including perception modules, planning systems, control units, and communication interfaces. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_02231 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Risk Assessment and Threat Modeling for safe autonomous driving technology Paz, Ian Alexis Wong Balan, Anuvinda Campos, Sebastian Orenstain, Ehud Dhakal, Sudip Cryptography and Security This research paper delves into the field of autonomous vehicle technology, examining the vulnerabilities inherent in each component of these transformative vehicles. Autonomous vehicles (AVs) are revolutionizing transportation by seamlessly integrating advanced functionalities such as sensing, perception, planning, decision-making, and control. However, their reliance on interconnected systems and external communication interfaces renders them susceptible to cybersecurity threats. This research endeavors to develop a comprehensive threat model for AV systems, employing OWASP Threat Dragon and the STRIDE framework. This model categorizes threats into Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service (DoS), and Elevation of Privilege. A systematic risk assessment is conducted to evaluate vulnerabilities across various AV components, including perception modules, planning systems, control units, and communication interfaces. |
| title | Risk Assessment and Threat Modeling for safe autonomous driving technology |
| topic | Cryptography and Security |
| url | https://arxiv.org/abs/2505.02231 |