Ontological Analysis of the Digital Crime Conceptual Model

A conceptual ontological model of Digital Crime has been developed, consisting of five non-empty classes. Identification and classification were carried out according to the experience of domestic and foreign experts. The central place of the model is occupied by objects of the Digital Crime class,...

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Bibliographic Details
Main Authors: Vlasenko, Lidiia, Lutska, Nataliia, Zaiets, Nataliia, Lysenko, Vitaliy
Format: Conference Proceeding
Language:English
Subjects:
Analytical models
Computational modeling
Computer science
criminal liability
Decision support systems
digital crime
digital evidence
Knowledge engineering
Ontologies
ontology
System integration
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Summary:A conceptual ontological model of Digital Crime has been developed, consisting of five non-empty classes. Identification and classification were carried out according to the experience of domestic and foreign experts. The central place of the model is occupied by objects of the Digital Crime class, which have their own attributes and are connected by various links with other objects. Objects of some classes are filled in by users, others are formed by knowledge engineers. Based on the ontological analysis, SWRL-rules are constructed that automatically form links between objects of the custom classes Digital crime and Digital evidence with objects of the Type of crime and Criminal Liability classes. The last class contains articles of the Criminal Code of Ukraine on criminal liability for digital crimes. The ontological model is developed taking into account possible requests to it. Such queries can be formed on the basis of direct relationships between human and automatic concepts. And also contain logical chains to concepts that do not contain an explicit link in the ontology. It is assumed that the model can be expanded and supplemented. The ontological model of Digital Crime can be used to share information, develop new systems and applications, improve information retrieval and ensure its accordance.
ISSN:2766-3639
DOI:10.1109/CSIT61576.2023.10324030