## 3 Related Works
They carried out a comparative review of different CTI enumeration and sharing standards and identified diverse metrics essential for shaping standard CTI taxonomies. Given the hurdles observed with popular cybersecurity taxonomies--such as limited integration and a lack of connections between taxonomies and ontologies--the authors introduced a standardized framework. This framework consolidates various taxonomies, aiming to bolster efficient vulnerability assessment capabilities and augment CTI efficacy. The suggested framework encompasses multiple stages, namely discover, prioritize, continuous evaluation, reporting, and remediation. Inline with their approach, they also touched upon the anticipated growth in the importance of CTI knowledge graphs stemming from the standardization process. [PERSON] in [23] conducted a mapping of the controls from ISO/IEC 27002:2013, ISO/IEC 27002:2022, the NIS Directive, and the GDPR. The primary aim was to guide organizations in properly implementing these regulations, pinpointing potential security concerns, and formulating new security strategies. [PERSON] in [24] formulated and showcased a security ontology delineating the connections among vulnerabilities, standards, and legal as well as regulatory mandates. This created resource can bolster the resilience of organizational assets and enhance security mitigation. The detailed relationships illustrate the manner and specific controls that address existing vulnerabilities while concurrently adhering to legal and regulatory stipulations. [PERSON] et al. in [25] introduced the CyberTOMP framework, a comprehensive tool that equips organizations with resources for holistic cybersecurity management on both tactical and operational fronts. A significant component of this framework is the Unified List of Expected Outcomes (ULEO), which offers a consistent listing of cybersecurity measures required to safeguard specific assets. Additionally, ULEO presents a set of metrics that, when combined, can assess the current cybersecurity status of assets, trace their progression over time, or set cybersecurity goals at various organizational levels. Notably, this proposition emphasizes procedural and methodological approaches rather than purely technical solutions. [PERSON] in [26] conducted a comparison between the NIST CSF and ISO 27001 cybersecurity frameworks, primarily examining their suitability and selection criteria. The study suggests that organizations should evaluate and adopt specific frameworks based on factors such as their risk maturity level, certification requirements, and a cost-benefit analysis. The authors in [27] introduced an automated technique that furthers ontology engineering and development to accurately depict security directives for automated verification. Impressively, the method ingeniously merges methodologies and tools from two recognized domains of informatics: Natural Language Processing (NLP) for POS tagging and ontology creation. This method is demonstrated through a tangible challenge: creating an automated representation of directives as ontologies, specifically for the latest European directive on cybersecurity, the NIS 2. The developed NIS 2 ontology followed a waterfall methodology, adhering to a set sequence of stages ranging from specification and implementation to evaluation, akin to traditional software development. [PERSON] et al. in [28] introduced an ontological approach for the characterization of security directives. The proposed structural solution supports the case that semantic representation of the NIS 2 Directive provides an effective method for compliance verification. The approach meets the FAIR principles and the NIS ONTOLOGY as it is termed may help security analysts to quickly verify the status of the institutions' compliance, resulting in an efficient search engine for security measures. The development of the model is currently ongoing toward a more complete coverage of the NIS 2 Directive, as its current version only covers articles 7 and 10 of the NIS 2. [PERSON] et al.