University of Twente Student Theses
Classifying ransomware victims’ nationalities based on leak page entries
Dop, L.T.J. (2023) Classifying ransomware victims’ nationalities based on leak page entries.
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| Abstract: | Ransomware is a type of malware that prevents a user from accessing their files by encrypting them. This is done to extort the victim. Some malware strains go beyond this and post the victim’s personal information and files online to add extra pressure to pay. Pages dedicated to the posting of such information are called leak pages. These leak pages can provide a lot of information about the victim, such as their nationality. In this research, a refined data set of features related to a victim’s nationality is created from a set of leak page entries. This data set is then used to train a classification model to classify a victim by country. Afterward, the results of this classification model are analyzed and it is shown that the model has a mean accuracy of 91% |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 54 computer science |
| Programme: | Computer Science BSc (56964) |
| Link to this item: | https://purl.utwente.nl/essays/95849 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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