Classifying the Dark Web: creating a robust Dark Web Ontology

Supervisors:

• CFLW: Eljo Haspels (eljo.haspels@cflw.com)
• KAI: Romana Pernisch (r.pernisch@vu.nl)

The selection process for this thesis has started and we do not accept any more applications.

Background:

Gaining insights starts with clear definitions. And although a lot of research has been done already on Open Source information on the Dark Web, a clear Ontology/Taxonomy is lacking in this domain. Some research has been done, for example: link. But more is needed to come to a well-defined way to classify the dark web which is needed to streamline collaboration and interoperability of systems.

Description:

Recently CFLW has begun the development of the Dark Web Ontology. This thesis research would be to solidify this draft and develop it into a solid foundation for the community to use.

Tasks:

1. What are ontology engineering best practices?
2. How can the ontology be shared according to standards?
3. How can the Dark Web Ontology of CFLW be improved?

Research Question: Are state-of-the-art ontology engineering principles applicable in the domain of the dark web?

Literature:

• Cybercrime threat intelligence: A systematic multi-vocal literature review [paper]
• Use of OWL and Semantic Web Technologies at Pinterest [paper]
• Finding the Pattern You Need: The Design Pattern Intent Ontology [paper]
• Ontology-Based Design Pattern Selection [paper]
• The NeOn Methodology for Ontology Engineering [paper]