Cybercrime Classification: A Victimology-based approach

Abstract

The need for understanding cybercrime and the possibility of its occurrence is significant to mitigate its adverse effects on society. A comprehensive universally agreed-upon classification scheme for cybercrime is hugely lacking in terms of utilizing a complete perspective of the entities involved in the same. A new perspective in cybercrime classification is moving beyond the machines and focusing on the humans, especially the victims. Cyber victimization extends from the single user to a mass or system perspective, thereby representing governments, organizations, and society to be categorized as victims. This paper proposes a novel ontological classification of cyber victimology that can help illustrate the complete cybercrime incident from the perspective of the victim. We utilize a multidimensional typology to represent the dimensions and classifications of the cybercrime victim. We then analyse the semantic relationships between the ontological objects to develop a comprehensive victimology representation. The understanding of the type and role of the victim provides new insight into the analysis of the cyber incident. Moreover, the resultant representation can serve as an extension to current cybercrime ontological frameworks and help in providing a new point of defence in cybercrime incidents. Finally, such a victimology-based classification can subsequently result in a dynamic ontology which can be queried to obtain relevant insights into the nature and occurrence of cybercrimes.