On Practicality of Using ARM TrustZone Trusted Execution Environment for Securing Programmable Logic Controllers
<|reference_start|>On Practicality of Using ARM TrustZone Trusted Execution Environment for Securing Programmable Logic Controllers: Programmable logic controllers (PLCs) are crucial devices for implementing automated control in various industrial control systems (ICS), such as smart power grids, water treatment systems, manufacturing, and transportation systems. Owing to their importance, PLCs are often the target of cyber attackers that are aiming at disrupting the operation of ICS, including the nation's critical infrastructure, by compromising the integrity of control logic execution. While a wide range of cybersecurity solutions for ICS have been proposed, they cannot counter strong adversaries with a foothold on the PLC devices, which could manipulate memory, I/O interface, or PLC logic itself. These days, many ICS devices in the market, including PLCs, run on ARM-based processors, and there is a promising security technology called ARM TrustZone, to offer a Trusted Execution Environment (TEE) on embedded devices. Envisioning that such a hardware-assisted security feature becomes available for ICS devices in the near future, this paper investigates the application of the ARM TrustZone TEE technology for enhancing the security of PLC. Our aim is to evaluate the feasibility and practicality of the TEE-based PLCs through the proof-of-concept design and implementation using open-source software such as OP-TEE and OpenPLC. Our evaluation assesses the performance and resource consumption in real-world ICS configurations, and based on the results, we discuss bottlenecks in the OP-TEE secure OS towards a large-scale ICS and desired changes for its application on ICS devices. Our implementation is made available to public for further study and research.<|reference_end|>
@article{li2024on,
    title={On Practicality of Using ARM TrustZone Trusted Execution Environment for
  Securing Programmable Logic Controllers},
    author={Zhiang Li, Daisuke Mashima, Wen Shei Ong, Ertem Esiner, Zbigniew
  Kalbarczyk, Ee-Chien Chang},
    journal={arXiv preprint arXiv:2403.05448},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.05448},
    primaryClass={cs.CR}
}