Stealthy Attacks against Robotic Vehicles Protected by Control-based Intrusion Detection Techniques
Open accessAbstract
Robotic vehicles (RV) are increasing in adoption in many industrial sectors. RVs use auto-pilot software for perception and navigation and rely on sensors and actuators for operating autonomously in the physical world. Control algorithms have been used in RVs to minimize the effects of noisy sensors, prevent faulty actuator output, and, recently, to detect attacks against RVs. In this article, we demonstrate the vulnerabilities in control-based intrusion detection techniques and propose three kinds of stealthy attacks that evade detection and disrupt RV missions. We also propose automated algorithms for performing the attacks without requiring the attacker to expend significant effort or to know specific details of the RV, thus making the attacks applicable to a wide range of RVs. We demonstrate the attacks on eight RV systems including three real vehicles in the presence of an Intrusion Detection System using control-based techniques to monitor RV’s runtime behavior and detect attacks. We find that the control-based techniques are incapable of detecting our stealthy attacks and that the attacks can have significant adverse impact on the RV’s mission (e.g., deviate it significantly from its target, or cause it to crash).
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Sorted by citations
Robotics cyber security: vulnerabilities, attacks, countermeasures, and recommendations
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- Authors
- Dash, P., Karimibiuki, M., & Pattabiraman, K.
- Affiliations
- University of British Columbia (CA)
- Venue
- Digital Threats: Research and Practice
- Published
- 2021-01-22
- Volume
- 2
- Issue
- 1
- Pages
- 1-25
- ISSN
- 2576-5337 (ISSN-L)
- 2692-1626
- OpenAlex
- W3125882489
- Cited by
- 40
- References
- 49
- Citations by year
- 2026: 8 · 2025: 10 · 2024: 6 · 2023: 8 · 2022: 3 · 2021: 5
- FWCI
- 1.93
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Digital Threats Research and Practice (publishedVersion)
- Funders
- Natural Sciences and Engineering Research Council of Canada
- Intel
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Adversarial Robustness in Machine Learning
- Physical Sciences › Engineering › Control and Systems Engineering › Smart Grid Security and Resilience
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Keywords
- robotic vehicle, stealthy attacks, attack evasion, actuator attacks, sensor attacks
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