Risk Assessment and Threat Modeling for safe autonomous driving technology

TL;DR

This paper develops a comprehensive threat model and risk assessment framework for autonomous vehicle systems, addressing cybersecurity vulnerabilities across perception, planning, control, and communication components.

Contribution

It introduces a novel threat modeling approach using OWASP Threat Dragon and STRIDE framework tailored for AV systems, enhancing cybersecurity risk management.

Findings

Identified key vulnerabilities in perception and communication modules.

Categorized threats into six main types using STRIDE.

Provided a systematic risk assessment methodology for AV components.

Abstract

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.