## 8 Conclusions and Future Directions
Two nodes of the Singapore University of Technology and Design and the Chinese Academy of Sciences are the leaders in collaboration. The tendency remains that bigger institutions have more research links to other countries, while smaller players have just one or two connections. All this shows that collaboration potential in the sphere of OT security, especially for smaller players, remains not used in full measure. * Analysis of keywords by frequency, links, and other parameters has shown that keywords such as 'Industrial Control System' in different forms, 'Anomaly Detection' with 'Intrusion Detection', and 'Machine Learning' are the most widely used. Keywords often \"overlap\". Also, the domination of \"general\" keywords shows may scientists just mark the importance of the area rather than suggesting a specific solution, maybe except the topic of attack/intrusion detection. OT is among the keywords used, but its popularity is much lower than the more common SCADA/ICS/PLC terms. The existence of some relatively distinct (not top-level) but topic-specific keywords, not typical for other information technology security areas such as 'ensemble learning', 'hardware trojan' and their detection, 'federated learning', 'transfer learning' demonstrate area-specific problems, specifics of OT architectural solutions and possible directions for research widening. * On the other hand, keyword burst detection analysis has identified an important trend, that 'operational technology' has a significant burst in the period 2023-2024. This is extremely important in the sense of this research since, as we could see from the previous analysis, more narrow topics of ICSs and SCADA were dominating the landscape, and the detected burst of OT potentially shows the shift in the research direction and wider understanding of the problem area. One more important shift that can be noticed in keyword burst is an increasing number of more specific keywords, such as'model', 'framework', 'cyber attacks', and 'vulnerability detection'. They show that researchers switch from just defining the problem to attempting to systemize the research area and deal with specific problems. It is a positive tendency, showing that research has reached the initial knowledge saturation level. * Finally, analysis of publication, author, and journal burst values demonstrates the increasing number of burst publications in the 2023-2024 period. This is extremely important since it can signify increased interest in the topic. One more important observation would be that more than 65% of researchers with high burst have obtained their evaluation in the period 2022/2023-2024. It is a positive tendency, showing the growing potential of new researchers and the case that despite the dominance of researchers from PRC, some authors from other countries, previously not noticed among the strongest (Pakistan, Israel, and South Korea) have obtained recognition in the research society. There is also a remarkable tendency that although earlier (prior to 2021) proceeding papers were obtaining the highest burst rate, starting from 2023, journals have made significant progress and become more attractive for publishing. This can be explained by the increasing popularity of open-access models and quick article processing, which are supported by some publishing houses. Based on an extensive bibliometric study of OT security research covering the years 2018 to 2024, it is recommended that upcoming research should concentrate on sophisticated machine learning approaches, ensemble learning, federated learning, transfer learning, and techniques specific to detecting OT-related attacks, including the identification of hardware trojans. Some trends show that there may be a need for domain-specific frameworks and models, while general-purpose research on the topic has reached saturation. One of the main problems that limit the research effectiveness remains the low collaboration level between nations, institutions, and research groups.