Optimizing Cybersecurity Ontology Matching

The intense transformations occurring in economic, political, and social scenarios have made information systems (IS) more complex. This complexity relates to a category of systems that involves the integration of cybernetic and physical components using sensor, computing, and network technologies, commonly referred to as Cyber-Physical Systems (CPS). The rapid growth of CPS applications leads to a series of security and confidentiality issues, particularly concerning their critical infrastructures and sensitive functionalities. These issues can be addressed through security domain ontologies. However, integrating them can also create opportunities for experienced attackers to exploit heterogeneity problems and inject malicious code into these systems. Therefore, this research project aims to develop an interactive ontology alignment program using the K-Means algorithm and three classifiers in machine learning to address the heterogeneity issues in the integration of ontologies within the nuclear power plant safety domain. This approach will enable the fully secure operation of integrated nuclear plant systems without the risk of cyberattacks