ML-KEM-768 latency analysis on IIoT systems in the context of post-quantum security

Authors

  • H.A Danang Rimbawa Universitas Pertahanan Republik Indonesia, Bogor, Indonesia
  • Danny Setyowati Universitas Pertahanan Republik Indonesia, Bogor, Indonesia
  • Achmad Farid Wadjdi Badan Riset dan Inovasi Nasional, Jakarta, Indonesia

DOI:

https://doi.org/10.35335/int.jo.emod.v20i2.185

Keywords:

Communication Performance, IIoT Security, Latency Analysis, ML-KEM-768, Post-Quantum Cryptography

Abstract

This study aims to analyze the performance of the Post Quantum Cryptography ML-KEM-768 algorithm in the Industrial Internet of Things system which has limited resources and communication stability needs. The approach used is a quantitative experiment with end-to-end latency measurement on a virtual machine-based architecture that represents IIoT system communication. The evaluation parameters included latency distribution, percentile values, and characteristics of steady state and spike conditions. The test results showed that the ML-KEM-768 had a median latency of 51.84 ms with a P95 value of 64.17 ms and a P99 of 76.85 ms, as well as a steady state proportion of above 96 percent. The spike latency condition persists with low frequency and does not affect the overall stability of the system. These results show that ML-KEM-768 can be implemented in IIoT systems with communication performance that remains within operational tolerance limits.

References

Alaba, F. A., Othman, M., Hashem, I. A., & Alotaibi, F. (2017). Internet of Things Security: A Survey. Journal of Network and Computer Applications, 88, 10–28. https://doi.org/10.1016/j.jnca.2017.04.002

Alghazali, M. (2024). IoT Security Threat Landscape. Sensors.

Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: A Survey. Computer Networks, 54(15), 2787–2805. https://doi.org/10.1016/j.comnet.2010.05.010

Bernstein, D. J., Buchmann, J., & Dahmen, E. (2017). Post-Quantum Cryptography. Nature, 549, 188–194. https://doi.org/10.1038/nature23461

Biryukov, A., & others. (2016). Lattice-Based Cryptography for Beginners. IEEE Security and Privacy, 14(6), 76–81. https://doi.org/10.1109/MSP.2016.124

Chen, L., & Misra, S. (2024). Post Quantum Cryptography and Its Applications. IEEE Communications Surveys and Tutorials.

Cover, T., & Thomas, J. (2021). Elements of Information Theory.

Dean, J., & Barroso, L. (2013). The Tail at Scale. Communications of the ACM.

Farooq, U. (2023). Security Challenges in IIoT. IEEE Access.

Goldsmith, A. (2020). Wireless Communications. Cambridge.

Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things: A Vision, Architectural Elements, and Future Directions. Future Generation Computer Systems, 29(7), 1645–1660. https://doi.org/10.1016/j.future.2013.01.010

Hubbard, D. (2020). How to Measure Cyber Risk. Cybersecurity Journal.

Humayed, A. (2020). Cyber Physical Systems Security. IEEE IoT Journal.

Jain, R. (1991). Computer Systems Performance Analysis. Wiley.

Kampanakis, P., Sikeridis, D., & Devetsikiotis, M. (2019). Post-Quantum Cryptography: Current State and Quantum Mitigation. IEEE Communications Surveys and Tutorials, 21(2), 1167–1196. https://doi.org/10.1109/COMST.2018.2845560

Linkov, I. (2021). Cyber Risk Framework. Risk Analysis.

Montgomery, D. (2017). Design and Analysis of Experiments.

Mosavi, A., & Gholipour, A. (2024). Quantum Threats to Cryptography. Future Internet.

NIST. (2024). Module Lattice Based Key Encapsulation Mechanism Standard.

O’Connor, T. (2023). Performance Analysis of PQC in IoT. Journal of Cybersecurity.

Rescorla, E. (2021). TLS 1.3 Protocol. RFC.

Roman, R., Zhou, J., & Lopez, J. (2013). Features and Challenges of Security in Internet of Things. Computer Networks, 57(10), 2266–2279. https://doi.org/10.1016/j.comnet.2012.12.018

Singh, R. (2023). Integration of AI and Security Systems. Journal of Information Security.

Stevens, M. (2024). Cyber Threats in Industrial Systems. Computers and Security.

Stouffer, K., & Pillitteri, V. (2022). Guide to Industrial Control Systems Security.

Tang, L. (2024). Performance Overhead of PQC Algorithms. IEEE Access.

Zhang, Q., Chen, M., & Li, L. (2014). Latency Analysis for Cloud Based IoT Applications. IEEE Cloud Computing, 1(2), 28–35. https://doi.org/10.1109/MCC.2014.35

Zhang, W., & Wang, L. (2025). AI Based Anomaly Detection in IoT. IEEE Transactions on AI.

Downloads

Published

2026-05-30

How to Cite

Rimbawa, H. D., Setyowati, D., & Wadjdi, A. F. (2026). ML-KEM-768 latency analysis on IIoT systems in the context of post-quantum security. International Journal of Enterprise Modelling, 20(2), 238244. https://doi.org/10.35335/int.jo.emod.v20i2.185