PHATO: Phishing Attack Ontology

PURL: https://purl.org/phishing-ontology

PHATO is a well-founded Phishing Attack Ontology, specified in OntoUML modeling language, built by reusing the Reference Ontology for Security Engineering.

The acronym plays with two related ideas: in Portuguese, ''phato'' may sound like ''fato'' (fact, in English) or like ''pato'' (duck). Phishing involves lying about the facts to deceive a target. Moreover, ''pato'' is slang meaning a naive person who is easily deceived.

Project Structure

• /ontouml contains files related to the conceptual version of PHATO, which is represented in OntoUML.

Reusing .vpp files

• To open and edit .vpp files, use Visual Paradigm

Built with

• Visual Paradigm - a UML CASE tool that offers a free community edition version
• The OntoUML Plugin for Visual Paradigm

Slide Presentation

• Click here.

Authors

• Ítalo Oliveira - Free University of Bozen-Bolzano, Bolzano, Italy | University of Twente, Enschede, Netherlands
• Rodrigo F. Calhau - University of Espírito Santo, Vitória, Brazil | University of Twente, Enschede, Netherlands
• Giancarlo Guizzardi - University of Twente, Enschede, Netherlands

References

• Oliveira, Í., Calhau, R. F., (2023). Toward a Phishing Attacks Ontology. ER2023: Companion Proceedings of the 42nd International Conference on Conceptual Modeling: ER Forum, 7th SCME, Project Exhibitions, Posters and Demos, and Doctoral Consortium, November 06-09, 2023, Lisbon, Portugal. https://ceur-ws.org/Vol-3618/forum_paper_25.pdf
• Baratella, R., Fumagalli, M., Oliveira, Í., Guizzardi, G. (2022). Understanding and Modeling Prevention. In: Guizzardi, R., Ralyté, J., Franch, X. (eds) Research Challenges in Information Science. RCIS 2022. Lecture Notes in Business Information Processing, vol 446. Springer, Cham. https://doi.org/10.1007/978-3-031-05760-1_23
• Oliveira, Í., Sales, T.P., Baratella, R., Fumagalli, M., Guizzardi, G. (2022). An Ontology of Security from a Risk Treatment Perspective. In: Ralyté, J., Chakravarthy, S., Mohania, M., Jeusfeld, M.A., Karlapalem, K. (eds) Conceptual Modeling. ER 2022. Lecture Notes in Computer Science, vol 13607. Springer, Cham. https://doi.org/10.1007/978-3-031-17995-2_26

Errata

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