Home / Current Issue / Paper 1707488
Cyber-resilient Construction: AI-powered Security and Its Impact on Automation & Labor Productivity
Subject area: Science,Engineering and Technology · Area of research: Artificial Intelligence in Healthcare
Abstract
The construction industry transition to digital processing has increased the importance of automated technologies and smart solutions therefore putting cybersecurity at the center. The attacks on construction projects through cyber means obstruct automated work sequences while endangering confidential information and adversely affecting job performance effectiveness. This paper evaluates how AI security technology improves cybersecurity capabilities in building projects. This paper explores the use of AI risks mitigation strategies which combine real-time threat indicators alongside intrusion blocking capabilities and blockchain protection for data security systems based for smart construction spaces. The paper investigates AI's automation ability and its employee productivity impact through a study of process optimization benefits alongside workforce teamwork promotion and cybersecurity protection methods which avoid operational losses. The paper introduces an artificial intelligence-based cybersecurity model for construction operations which handles system scalability as well as integration needs. AI-powered security mechanisms will create a future of increased resilience combined with productivity and security which follows cybersecurity regulations properly.
Keywords
Cyber-Resilient Construction, AI-Powered Security in Construction, Automation and Cybersecurity in Construction, AI-Driven Risk Mitigation in Construction, Impact of AI on Labor Productivity
References
[1] Abbas, A. (2025). Artificial Intelligence in Construction Risk Management: Improving Safety and Efficiency in Smart City Development.
[2] Alijoyo, F. A. (2024). AI-powered deep learning for sustainable industry 4.0 and internet of things: Enhancing energy management in smart buildings. Alexandria Engineering Journal, 104, 409-422.https://doi.org/10.1016/j.aej.2024.07.110
[3] Amer, N., & Nagy, G. (2024, September). Smart Materials for Modern Facades: An AI-Powered Selection Process. In IOP Conference Series: Earth and Environmental Science (Vol. 1396, No. 1, p. 012014). IOP Publishing. https://doi.org/10.1088/1755-1315/1396/1/012014
[4] Akhtar, Z. B., & Rawol, A. T. (2024). Enhancing cybersecurity through AI-powered security mechanisms. IT Journal Research and Development, 9(1), 50-67. https://doi.org/10.25299/itjrd.2024.16852
[5] Aakassh, S., Prasad, P. W. C., & Seher, I. (2023, November). Constructing a Proactive Cyber Resilient Culture for Better Business Outcomes. In Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (pp. 55-68). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-71773-4_5
[6] Al-Janabi, S., Jabbar, H., & Syms, F. (2024). Cybersecurity Transformation: Cyber-Resilient IT Project Management Framework. Digital, 4(4).
[7] Bellini, E., Marrone, S., & Marulli, F. (2021). Cyber resilience meta-modelling: The railway communication case study. Electronics, 10(5), 583. https://doi.org/10.3390/electronics10050583
[8] Bonsay, J. O., Cruz, A. P., Firozi, H. C., & Camaro, P. J. C. (2021). Artificial intelligence and labor productivity paradox: The economic impact of AI in China, India, Japan, and Singapore. Journal of Economics, Finance and Accounting Studies, 3(2), 120-139.
[9] Belchik, T. A. (2021). Artificial intelligence as a factor in labor productivity. In Сooperation and Sustainable Development (pp. 525-535). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-77000-6_62
[10] Coppolino, L., Nardone, R., Petruolo, A., & Romano, L. (2023). Building cyber-resilient smart grids with digital twins and data spaces. Applied Sciences, 13(24), 13060. https://doi.org/10.3390/app132413060
[11] d’Ambrosio, N., Perrone, G., Romano, S. P., & Urraro, A. (2025). A cyber-resilient open architecture for drone control. Computers & Security, 150, 104205. https://doi.org/10.1016/j.cose.2024.104205
[12] Damioli, G., Van Roy, V., & Vertesy, D. (2021). The impact of artificial intelligence on labor productivity. Eurasian Business Review, 11, 1-25. https://doi.org/10.1007/s40821-020-00172-8
[13] Emaminejad, N., Kath, L., & Akhavian, R. (2024). Assessing trust in construction ai-powered collaborative robots using structural equation modeling. Journal of Computing in Civil Engineering, 38(3), 04024011. https://doi.org/10.1061/JCCEE5.CPENG-5660
[14] Fisk, D. (2012). Cyber security, building automation, and the intelligent building. Intelligent Buildings International, 4(3), 169-181. https://doi.org/10.1080/17508975.2012.695277
[15] Frank, M. R., Autor, D., Bessen, J. E., Brynjolfsson, E., Cebrian, M., Deming, D. J., ... & Rahwan, I. (2019). Toward understanding the impact of artificial intelligence on labor. Proceedings of the National Academy of Sciences, 116(14), 6531-6539. https://doi.org/10.1073/pnas.1900949116
[16] Gado, N. G. (2024). AI Revolutionizes Construction Management “Building Smarter, Safer, and Efficiently Addressing Industry Challenges”. Engineering Research Journal, 183(3), 330-344.
[17] Gado, N. G. (2024). AI Revolutionizes Construction Management “Building Smarter, Safer, and Efficiently Addressing Industry Challenges”. Engineering Research Journal, 183(3), 330-344. https://doi.org/10.1007/978-3-031-51719-8_16
[18] Haider, Z. (2025). Health and Safety in Construction: Evaluating Workplace Hazards for Masons through AI-Driven Risk Management.
[19] Illiashenko, O., Kharchenko, V., Babeshko, I., Fesenko, H., & Di Giandomenico, F. (2023). Security-informed safety analysis of autonomous transport systems considering AI-powered cyberattacks and protection. Entropy, 25(8), 1123. https://doi.org/10.3390/e25081123
[20] Khalid, J., Chuanmin, M., Altaf, F., Shafqat, M. M., Khan, S. K., & Ashraf, M. U. (2024). AI-Driven Risk Management and Sustainable Decision-Making: Role of Perceived Environmental Responsibility. Sustainability, 16(16), 6799. https://doi.org/10.3390/su16166799
[21] Lysenko, S. E. R. G. I. I., Sokalskyi, D. M. Y. T. R. O., & Mykhasko, I. A. N. A. (2021). Methods for cyberattacks detection in the computer networks as a mean of resilient IT-infrastructure construction: state-of-art.
[22] Meng, B., Larraz, D., Siu, K., Moitra, A., Interrante, J., Smith, W., ... & Chowdhury, O. (2021). Verdict: a language and framework for engineering cyber resilient and safe system. Systems, 9(1), 18. https://doi.org/10.3390/systems9010018
[23] Mehmood, A., Epiphaniou, G., Maple, C., Ersotelos, N., & Wiseman, R. (2023). A hybrid methodology to assess cyber resilience of iot in energy management and connected sites. Sensors, 23(21), 8720. https://doi.org/10.3390/s23218720
[24] Moayyed, H., Moradzadeh, A., Mansour-Saatloo, A., Mohammadi-Ivatloo, B., Abapour, M., & Vale, Z. (2023). A global cyber-resilient model for dynamic line rating forecasting based on deep federated learning. IEEE Systems Journal, 17(4), 6390-6400. https://doi.org/10.1109/JSYST.2023.3287413
[25] Mantha, B. R., & García de Soto, B. (2021). Cybersecurity in construction: Where do we stand and how do we get better prepared. Frontiers in Built Environment, 7, 612668. https://doi.org/10.3389/fbuil.2021.612668
[26] Mantha, B. R., & García de Soto, B. (2021). Assessment of the cybersecurity vulnerability of construction networks. Engineering, Construction and Architectural Management, 28(10), 3078-3105. https://doi.org/10.1108/ECAM-06-2020-0400
[27] Nyamuchiwa, K., Lei, Z., & Aranas Jr, C. (2022). Cybersecurity vulnerabilities in off-site construction. Applied Sciences, 12(10), 5037. https://doi.org/10.3390/app12105037
[28] Prabha, B. V., Yasotha, B., Jaisudha, J., Senthilkumar, C., & Pandi, V. S. (2023, November). Enhancing Residential Security with AI-Powered Intrusion Detection Systems. In 2023 International Conference on Sustainable Communication Networks and Application (ICSCNA) (pp. 1510-1515). IEEE. https://doi.org/10.1109/ICSCNA58489.2023.10370042
[29] Plevris, V. (2024). AI-driven innovations in earthquake risk mitigation: a future-focused perspective. Geosciences, 14(9), 244.
[30] Ross, R., Pillitteri, V., Graubart, R., Bodeau, D., & McQuaid, R. (2019). Developing cyber resilient systems: a systems security engineering approach (No. NIST Special Publication (SP) 800-160 Vol. 2 (Draft)). National Institute of Standards and Technology. https://doi.org/10.6028/NIST.SP.800-160v2
[31] Raj, M., & Seamans, R. (2018). Artificial intelligence, labor, productivity, and the need for firm-level data. In The economics of artificial intelligence: An agenda (pp. 553-565). University of Chicago Press.
[32] Raja, S. R., Devi, T. R., Raj, J. R. F., Sankar, V. K., Krishnan, R. S., & Venkatalakshmi, R. (2024, October). AI-Powered IoT Framework for Enhancing Building Safety through Stability Detection. In 2024 8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC) (pp. 73-80). IEEE. https://doi.org/10.1109/I-SMAC61858.2024.10714838
[33] Sonkor, M. S., & García de Soto, B. (2021). Operational technology on construction sites: A review from the cybersecurity perspective. Journal of Construction Engineering and Management, 147(12), 04021172. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002193
[34] Sina, F. (2025). Enhancing Construction Safety Behavior: AI-Based Strategies for Workplace Hazard Prevention and Risk Mitigation.
[35] Seamans, R., & Raj, M. (2018). AI, labor, productivity and the need for firm-level data (No. w24239). National Bureau of Economic Research.
[36] Salami Pargoo, N., & Ilbeigi, M. (2023). A scoping review for cybersecurity in the construction industry. Journal of Management in Engineering, 39(2), 03122003. https://doi.org/10.1061/JMENEA.MEENG-5034
[37] Shishehgarkhaneh, M. B., Moehler, R. C., Fang, Y., Aboutorab, H., & Hijazi, A. A. (2024). Construction supply chain risk management. Automation in Construction, 162, 105396.
[38] Sonkor, M. S., & de Soto, B. G. (2021). Is your construction site secure? A view from the cybersecurity perspective. In ISARC. Proceedings of the International Symposium on Automation and Robotics in Construction (Vol. 38, pp. 864-871). IAARC Publications.
[39] Tamoor, M., Imran, H. M., & Chaudhry, I. G. (2023). Revolutionizing construction site safety through artificial intelligence. Journal of Development and Social Sciences, 4(3), 1099-1104. https://doi.org/10.47205/jdss.2023(4-III)103
[40] Turk, Ž., de Soto, B. G., Mantha, B. R., Maciel, A., & Georgescu, A. (2022). A systemic framework for addressing cybersecurity in construction. Automation in Construction, 133, 103988. https://doi.org/10.1016/j.autcon.2021.103988
[41] Usama, M., Ullah, U., Muhammad, Z., Islam, T., & saba Hashmi, S. (2024). AI-Enabled Risk Assessment and Safety Management in Construction. In Ethical Artificial Intelligence in Power Electronics (pp. 105-132). CRC Press.
[42] Xu, G., & Guo, T. (2025). Advances in AI-powered civil engineering throughout the entire lifecycle. Advances in Structural Engineering, 13694332241307721. https://doi.org/10.1177/13694332241307721
[43] Yousaf, A. (2025). Collaborative Project Delivery and Innovation in Construction Management: AI’s Role in Optimizing Project Outcomes.
[44] Yousaf, A. (2025). Collaborative Project Delivery and Innovation in Construction Management: AI’s Role in Optimizing Project Outcomes.
[45] Zhao, P., Cao, Z., Zeng, D. D., Gu, C., Wang, Z., Xiang, Y., ... & Li, S. (2021). Cyber-resilient multi-energy management for complex systems. IEEE Transactions on Industrial Informatics, 18(3), 2144-2159.https://doi.org/10.1109/TII.2021.3097760
How to cite this paper
@article{1707488,
author = {Maliha Zaman Nizum},
title = {Cyber-resilient Construction: AI-powered Security and Its Impact on Automation & Labor Productivity},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {8},
number = {9},
pages = {440-455},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1707488.pdf},
abstract = {The construction industry transition to digital processing has increased the importance of automated technologies and smart solutions therefore putting cybersecurity at the center. The attacks on construction projects through cyber means obstruct automated work sequences while endangering confidential information and adversely affecting job performance effectiveness. This paper evaluates how AI security technology improves cybersecurity capabilities in building projects. This paper explores the use of AI risks mitigation strategies which combine real-time threat indicators alongside intrusion blocking capabilities and blockchain protection for data security systems based for smart construction spaces. The paper investigates AI's automation ability and its employee productivity impact through a study of process optimization benefits alongside workforce teamwork promotion and cybersecurity protection methods which avoid operational losses. The paper introduces an artificial intelligence-based cybersecurity model for construction operations which handles system scalability as well as integration needs. AI-powered security mechanisms will create a future of increased resilience combined with productivity and security which follows cybersecurity regulations properly.},
keywords = {Cyber-Resilient Construction, AI-Powered Security in Construction, Automation and Cybersecurity in Construction, AI-Driven Risk Mitigation in Construction, Impact of AI on Labor Productivity},
month = {March},
}