Abstract
CNC machines are largely used in production plants and constitute a critical asset for organizations globally. The strong push dictated by the Industry 4.0 paradigm led to the introduction of technologies for the wide connectivity of industrial equipment. As a result, modern CNCs resemble more to fully fledged systems rather than mechanical machines, offering numerous networking services for smart connectivity. This work explores the risks associated with the strong technological development observed in the domain of CNC machines. We performed an empirical evaluation of four representative controller manufacturers, by analyzing the technologies introduced to satisfy the needs of the Industry 4.0 paradigm, and conducting a series of practical attacks against real-world CNC installations. Our findings revealed that malicious users could abuse of such technologies to conduct attacks like denial-of-service, damage, hijacking or data theft. We reported our findings to the affected controller vendors and proposed mitigation. This work wants to be an opportunity to raise awareness in a domain in which, unfortunately, security doesn’t seem to be, yet, an important driver.
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Notes
- 1.
Some attacks are reported multiple times because consisting of attack variations. For example, a malicious user can modify the geometry of a tool to achieve damage, hijacking, or denial-of-service - depending on the type of machine and manufacturing process.
Vice versa, the same user can conduct several attacks to achieve the same goal. For example, an attacker can take control of the production of an exposed CNC by hijacking a parametric program, by modifying the geometry of a tool to introduce a micro-defect, or by changing the executed program.
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Balduzzi, M., Sortino, F., Castello, F., Pierguidi, L. (2023). An Empirical Evaluation of CNC Machines in Industry 4.0 (Short Paper). In: Hämmerli, B., Helmbrecht, U., Hommel, W., Kunczik, L., Pickl, S. (eds) Critical Information Infrastructures Security. CRITIS 2022. Lecture Notes in Computer Science, vol 13723. Springer, Cham. https://doi.org/10.1007/978-3-031-35190-7_5
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DOI: https://doi.org/10.1007/978-3-031-35190-7_5
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