Social Engineering in Cybersecurity: A Domain Ontology and Knowledge Graph Application Examples
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Abstract (arXiv)
Social engineering has posed a serious threat to cyberspace security. To protect against social engineering attacks, a fundamental work is to know what constitutes social engineering. This paper first develops a domain ontology of social engineering in cybersecurity and conducts ontology evaluation by its knowledge graph application. The domain ontology defines 11 concepts of core entities that significantly constitute or affect social engineering domain, together with 22 kinds of relations describing how these entities related to each other. It provides a formal and explicit knowledge schema to understand, analyze, reuse and share domain knowledge of social engineering. Furthermore, this paper builds a knowledge graph based on 15 social engineering attack incidents and scenarios. 7 knowledge graph application examples (in 6 analysis patterns) demonstrate that the ontology together with knowledge graph is useful to 1) understand and analyze social engineering attack scenario and incident, 2) find the top ranked social engineering threat elements (e.g. the most exploited human vulnerabilities and most used attack mediums), 3) find potential social engineering threats to victims, 4) find potential targets for social engineering attackers, 5) find potential attack paths from specific attacker to specific target, and 6) analyze the same origin attacks.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 28 May 2021.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 1; 2025: 2; 2026: 1.
5 papers.
- 2024Untargeted Adversarial Attack on Knowledge Graph Embeddingscited by 3
- 2025The AI Model Risk Catalog: What Developers and Researchers Miss About Real-World AI Harmscited by 3
- 2022Threat Detection for General Social Engineering Attack Using Machine Learning Techniquescited by 0
- 2025DASH: Deception-Augmented Shared Mental Model for a Human-Machine Teaming Systemcited by 0
- 2026Improving Interoperability among Defence and National Security Ontologies: Analysis and Evaluation Taskscited by 0
- 2026Improving Interoperability among Defence and National Security Ontologies: Analysis and Evaluation Tasks6 Aug 2026
- 2025DASH: Deception-Augmented Shared Mental Model for a Human-Machine Teaming System21 Dec 2025
- 2025The AI Model Risk Catalog: What Developers and Researchers Miss About Real-World AI Harms21 Aug 2025
- 2024Untargeted Adversarial Attack on Knowledge Graph Embeddings8 May 2024
- 2022Threat Detection for General Social Engineering Attack Using Machine Learning Techniques15 Mar 2022