Unlocking the Potential of Knowledge Graphs: A Cyber Defense Ontology for a Knowledge Representation and Reasoning System
Authors: 
José María Jorquera Valero, Antonio López Martínez, Pedro Miguel Sánchez Sánchez, Daniel Navarro Martínez, Rodrigo Varas López, Javier Ignacio Rojo Lacal, Antonio López Vivar, Marco Antonio Sotelo Monge, Manuel Gil Pérez, Gregorio Martínez PérezAuthors Info & Claims
ARES '24: Proceedings of the 19th International Conference on Availability, Reliability and Security
Article No.: 73, Pages 1 - 9
Abstract
In today’s dynamic and complex warfare landscape, characterized by the convergence of traditional and emerging threats, the significance of cybersecurity in shaping modern conflicts cannot be overstated. Such trend presents a challenging paradigm shift in how military organizations approach mosaic warfare in the digital age since new attack vectors and targets appear in their landscapes. In this vein, it is pivotal for military teams to have a clear and concise roadmap for cybersecurity incidents linked to potential mosaic warfare. This manuscript introduces a novel approach to bolstering mosaic warfare strategies by integrating an advanced Knowledge Representation and Reasoning system and a tailored ontology. Motivated by the critical role of cybersecurity in contemporary warfare, the proposed system aims to enhance situational awareness, decision-making capabilities, and operational effectiveness in the face of evolving cyber threats. In this sense, this manuscript entails a new ontology that not only covers the cybersecurity realm but also introduces key concepts related to strategic and operational military levels at the same time. The ad-hoc ontology is also compared against other well-known ones, such as MITRE, NATO, or UCO approaches and manifests a significant performance by employing standardized quality metrics for ontologies. Lastly, a realistic mosaic warfare scenario is contextualized to demonstrate the deployment of the proposed system and how it can properly represent all information gathered from heterogeneous data sources.
References
[1]
Ryszard Antkiewicz, Mariusz Chmielewski, Tomasz Drozdowski, Andrzej Najgebauer, Jarosław Rulka, Zbigniew Tarapata, Roman Wantoch-Rekowski, and Dariusz Pierzchała. 2012. Knowledge-Based Approach for Military Mission Planning and Simulation. In Advances in Knowledge Representation. IntechOpen.
[2]
Noam Ben-Asher, Alessandro Oltramari, Robert F Erbacher, and Cleotilde Gonzalez. 2015. Ontology-based Adaptive Systems of Cyber Defense. In STIDS. 34–41.
[3]
Ben De Meester, Pieter Heyvaert, Thomas Delva. 2024. RDF Mapping Language. Accessed on: May 6, 2024.
[4]
Xiaojun Chen, Shengbin Jia, and Yang Xiang. 2020. A review: Knowledge reasoning over knowledge graph. Expert systems with applications 141 (2020), 112948.
[5]
Edward A Cranford, Cleotilde Gonzalez, Palvi Aggarwal, Sarah Cooney, Milind Tambe, and Christian Lebiere. 2020. Toward personalized deceptive signaling for cyber defense using cognitive models. Topics in Cognitive Science 12, 3 (2020), 992–1011.
[6]
James P Delgrande, Birte Glimm, Thomas Meyer, Miroslaw Truszczynski, and Frank Wolter. 2023. Current and future challenges in knowledge representation and reasoning. arXiv preprint arXiv:2308.04161 (2023).
[7]
Hasra Dodampegama and Mohan Sridharan. 2023. Knowledge-based reasoning and learning under partial observability in ad hoc teamwork. Theory and Practice of Logic Programming 23, 4 (2023), 696–714.
[8]
Shaker H Ali El-Sappagh, Abdeltawab M Ahmed Hendawi, and Ali Hamed El Bastawissy. 2011. A proposed model for data warehouse ETL processes. Journal of King Saud University-Computer and Information Sciences 23, 2 (2011), 91–104.
[9]
Geographic Markup Language. 2024. GML Web. Accessed on: May 6, 2024.
[10]
Robert P Goldman, Mark Burstein, and Ugur Kuter. 2015. Knowledge Representation for Dynamic Formation of Sensing Goals in Cyber Defense. In Goal Reasoning: Papers from the ACS Workshop. 68.
[11]
Mary Haley. 2014. Information technology and the quality improvement in defense industries. The TQM Journal 26, 4 (2014), 348–359.
[12]
Martin Husák, Václav Bartoš, Pavol Sokol, and Andrej Gajdoš. 2021. Predictive methods in cyber defense: Current experience and research challenges. Future Generation Computer Systems 115 (2021), 517–530.
[13]
Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, and S Yu Philip. 2021. A survey on knowledge graphs: Representation, acquisition, and applications. IEEE transactions on neural networks and learning systems 33, 2 (2021), 494–514.
[14]
Peter E Kaloroumakis and Michael J Smith. 2021. Toward a knowledge graph of cybersecurity countermeasures. The MITRE Corporation 11 (2021).
[15]
Francesco Marchiori, Mauro Conti, and Nino Vincenzo Verde. 2023. STIXnet: A Novel and Modular Solution for Extracting All STIX Objects in CTI Reports. Association for Computing Machinery, New York, NY, USA, Article 3, 11 pages. https://doi.org/10.1145/3600160.3600182
[16]
NATO Science and Technology Organization. 2024. Knowledge Representation and Reasoning – A Review of the State of the Art and Future Opportunities. Technical Report. NATO Science and Technology Organization. https://www.sto.nato.int/Lists/STONewsArchive/displaynewsitem.aspx?ID=622 Accessed on: May 6, 2024.
[17]
Dat Tien Nguyen and Hao Duc Do. 2021. Research on Large-Scale Knowledge Base Management Frameworks for Open-Domain Question Answering Systems. In Intelligent Systems and Networks: Selected Articles from ICISN 2021, Vietnam. Springer, 87–92.
[18]
UCO Project. [n. d.]. Unified Cyber Ontology. https://github.com/ucoProject/UCO/tree/master. Accessed on: May 6, 2024.
[19]
Manuel Quesada-Martınez, Astrid Duque-Ramos, and Jesualdo Tomas Fernandez-Breis. 2015. Analysis of the evolution of ontologies using OQuaRE: Application to EDAM. In Proceedings of the international conference on biomedical ontology. 62–66.
[20]
Mohamed Saad, Yingzhong Zhang, Jinghai Tian, and Jia Jia. 2023. A graph database for life cycle inventory using Neo4j. Journal of Cleaner Production 393 (2023), 136344.
[21]
Leslie F Sikos, Dean Philp, Catherine Howard, Shaun Voigt, Markus Stumptner, and Wolfgang Mayer. 2019. Knowledge representation of network semantics for reasoning-powered cyber-situational awareness. AI in Cybersecurity (2019), 19–45.
[22]
Leslie F Sikos, Markus Stumptner, Wolfgang Mayer, Catherine Howard, Shaun Voigt, and Dean Philp. 2018. Automated reasoning over provenance-aware communication network knowledge in support of cyber-situational awareness. In Knowledge Science, Engineering and Management: 11th International Conference, KSEM 2018, Changchun, China, August 17–19, 2018, Proceedings, Part II 11. Springer, 132–143.
[23]
Vocabulary for Event Recording and Incident Sharing. 2024. VERIS Framework. https://verisframework.org/index.html Accessed on: May 6, 2024.
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- Unlocking the Potential of Knowledge Graphs: A Cyber Defense Ontology for a Knowledge Representation and Reasoning System
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July 2024
2032 pages
ISBN:9798400717185
DOI:10.1145/3664476
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Published: 30 July 2024
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- Spanish National Institute of Cybersecurity (INCIBE) by the Recovery, Transformation, and Resilience Plan, Next Generation EU
- European Defence Fund
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ARES 2024
ARES 2024: The 19th International Conference on Availability, Reliability and Security
July 30 - August 2, 2024
Vienna, Austria
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