The week's pick
Random Articles
Reseach Article
A Decoy Placement Model for Engineering Workstations and Historian Systems in Manufacturing OT Networks
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 187 - Number 127 |
| Year of Publication: 2026 |
| Authors: Daniel Ward |
10.5120/ijca54a0f5aecad7
|
Daniel Ward . A Decoy Placement Model for Engineering Workstations and Historian Systems in Manufacturing OT Networks. International Journal of Computer Applications. 187, 127 ( Jul 2026), 53-61. DOI=10.5120/ijca54a0f5aecad7
Abstract
Engineering workstations and historian systems concentrate control-project artifacts, privileged maintenance paths, and process knowledge in manufacturing operational technology (OT) networks. This paper develops and evaluates a safety-constrained decoy placement model for those assets. The revised study combines design science with a reproducible computational experiment built on a 26-node, 54-edge directed manufacturing OT attack graph. Six attack scenarios were tested against a no-deception baseline and four equal-budget alternatives: demilitarized-zone-heavy, random, betweenness-centrality, and asset-proximal placement. Each strategy was evaluated with 10,000 Monte Carlo trials per scenario under a five-decoy budget, resulting in 360,000 nominal trials with an arbitrary fixed seed of 314159. The proposed distributed placement achieved weighted pre-impact detection of 0.639 (95% CI 0.636-0.643), compared with 0.587 for asset-proximal placement, 0.574 for centrality placement, 0.411 for random placement, 0.356 for DMZ-heavy placement, and 0.122 for the baseline. Critical-target reach declined to 0.361. The advantage remained under reduced-fidelity and attacker-policy sensitivity tests. The results support distributed, high-value placement across remote access, engineering, project-file, historian, and protocol-discovery paths. The experiment is synthetic and does not claim live-plant effectiveness, but it provides falsifiable, reproducible evidence for comparative placement decisions.
References
- D. Ward, "Enhancing Security: A Comprehensive Study on Deception Technology Integration in Manufacturing and Critical Infrastructure," Ph.D. dissertation, University of the Cumberlands, Williamsburg, KY, USA, 2025. Available: https://www.proquest.com/openview/ebf38e1aa599115548a9f7486917e669/1
- K. A. Stouffer, M. Pease, C. Y. Tang, T. Zimmerman, V. Y. Pillitteri, S. Lightman, A. Hahn, S. Saravia, A. Sherule, and M. Thompson, "Guide to Operational Technology (OT) Security," NIST Special Publication 800-82, Rev. 3, 2023. doi: 10.6028/NIST.SP.800-82r3.
- National Institute of Standards and Technology, "The NIST Cybersecurity Framework (CSF) 2.0," NIST Cybersecurity White Paper 29, 2024. doi: 10.6028/NIST.CSWP.29.
- International Electrotechnical Commission, "IEC 62443-2-1:2024, Security for Industrial Automation and Control Systems - Part 2-1: Security Program Requirements for IACS Asset Owners," 2024. Available: https://webstore.iec.ch/en/publication/62883
- Cybersecurity and Infrastructure Security Agency, "Cross-Sector Cybersecurity Performance Goals, Version 2.0," 2025. Available: https://www.cisa.gov/cross-sector-cybersecurity-performance-goals
- MITRE, "ATT&CK for ICS Matrix," ATT&CK, 2026. Available: https://attack.mitre.org/matrices/ics/
- J. Franco, A. Aris, B. Canberk, and A. S. Uluagac, "A Survey of Honeypots and Honeynets for Internet of Things, Industrial Internet of Things, and Cyber-Physical Systems," IEEE Communications Surveys & Tutorials, vol. 23, no. 4, pp. 2351-2383, 2021. doi: 10.1109/COMST.2021.3106669.
- S. Maesschalck, V. Giotsas, B. Green, and N. Race, "Don't Get Stung, Cover Your ICS in Honey: How Do Honeypots Fit within Industrial Control System Security," Computers & Security, vol. 114, art. 102598, 2022. doi: 10.1016/j.cose.2021.102598.
- E. Lopez-Morales, C. Rubio-Medrano, A. Doupe, Y. Shoshitaishvili, R. Wang, T. Bao, and G. J. Ahn, "HoneyPLC: A Next-Generation Honeypot for Industrial Control Systems," in Proc. ACM SIGSAC Conf. Computer and Communications Security, 2020, pp. 279-291. doi: 10.1145/3372297.3423356.
- M. Lucchese, F. Lupia, M. Merro, F. Paci, N. Zannone, and A. Furfaro, "HoneyICS: A High-Interaction Physics-Aware Honeynet for Industrial Control Systems," in Proc. 18th Int. Conf. Availability, Reliability and Security, 2023, art. 113. doi: 10.1145/3600160.3604984.
- L. Salazar, E. Lopez-Morales, J. Lozano, C. Rubio-Medrano, and A. A. Cardenas, "ICSNet: A Hybrid-Interaction Honeynet for Industrial Control Systems," in Proc. Sixth Workshop on CPS&IoT Security and Privacy, 2024, pp. 68-79. doi: 10.1145/3690134.3694813.
- A. Javadpour, F. Ja'fari, T. Taleb, M. Shojafar, and C. Benzaid, "A Comprehensive Survey on Cyber Deception Techniques to Improve Honeypot Performance," Computers & Security, vol. 140, art. 103792, 2024. doi: 10.1016/j.cose.2024.103792.
- D. Ward, "Operationalizing Deception Technology in ICS/OT: A Control Mapping Framework for Critical Infrastructure Cybersecurity," International Journal of Soft Computing and Engineering, vol. 16, no. 3, pp. 1-9, 2026. doi: 10.35940/ijsce.C3723.16030726.
- D. Ward, "Decoy-Assisted Detection Metrics for Manufacturing Operational Technology Networks," International Journal of Scientific and Research Publications, vol. 16, no. 6, pp. 330-333, 2026. doi: 10.29322/IJSRP.16.06.2026.p17419.
- C. R. Harris et al., "Array Programming with NumPy," Nature, vol. 585, pp. 357-362, 2020. doi: 10.1038/s41586-020-2649-2.
- A. A. Hagberg, D. A. Schult, and P. J. Swart, "Exploring Network Structure, Dynamics, and Function Using NetworkX," in Proc. 7th Python in Science Conf., 2008, pp. 11-15. Available: https://networkx.org/
Index Terms
Keywords