RTOS Hardware Integrity Threat Detection Based on Quantitative Behavior Patterns 


Vol. 15,  No. 4, pp. 290-297, Apr.  2026
https://doi.org/10.3745/TKIPS.2026.15.4.290


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  Abstract

The expansion of RTOS adoption in embedded systems has led to an increase in security threats caused by various types of attacks. Attackers attempt to compromise systems not only by exploiting software vulnerabilities but also through hardware-based access using external interfaces, which may affect system operation. Various techniques have been proposed to detect such attacks; however, internal modifications for driver- or kernel-level monitoring may degrade real-time performance and the stability of existing system behavior due to additional overhead. Therefore, this paper proposes a method that detects anomalies by modeling performance indicators observed during system operation as behavioral fingerprints without modifying the internal system. To evaluate the proposed method, experimental tasks and attack scenarios were constructed, and changes in the indicators were observed.

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[IEEE Style]

Y. Ha, S. Ahn, K. Park, "RTOS Hardware Integrity Threat Detection Based on Quantitative Behavior Patterns," The Transactions of the Korea Information Processing Society, vol. 15, no. 4, pp. 290-297, 2026. DOI: https://doi.org/10.3745/TKIPS.2026.15.4.290.

[ACM Style]

Young-Bin Ha, Sung-Kyu Ahn, and Ki-Woong Park. 2026. RTOS Hardware Integrity Threat Detection Based on Quantitative Behavior Patterns. The Transactions of the Korea Information Processing Society, 15, 4, (2026), 290-297. DOI: https://doi.org/10.3745/TKIPS.2026.15.4.290.

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