A corpus database for cybersecurity topic modeling in the construction industry

In the digitalized era of Construction 4.0, ensuring the confidentiality, availability, and integrity of digital assets through cybersecurity is crucial for the construction industry. Although more than 75% of respondents from a Forrester survey who are in the construction, engineering, and infrastructure industries reported to have experienced a cyber-incident in the past 12 months, only 0.25% of cybersecurity publications focus on the construction industry until Jan 2023. Considering the significance of ensuring cybersecurity in construction, this study uses Latent Dirichlet Allocation (LDA) Topic Modeling technique to identify potential research directions in cybersecurity in the construction industry, based on various text sources collected, including news, articles & blogs, academic publications, books, standards, and company reports. The results of the study identify eight topics for future research: Perform Risk Analysis, Prevent the Increasing Cyber Incidents, Detect Ransomware, Strengthen Management Process, Protect Network Devices, Regulate Information Storage and Sharing, Protect Privacy, and Improve Authentication Process. Additionally, the corresponding action is proposed for addressing each topic. These findings can be used by researchers, practitioners, and policymakers in the construction industry to address the challenges and opportunities in cybersecurity.