Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/1696
Title: Cybercrime Offences: Identification, Classification and Adaptive Response
Authors: Tsakalidis, George
Vergidis, Kostas
Madas, Michael
Type: Conference Paper
Subjects: FRASCATI::Natural sciences::Computer and information sciences
FRASCATI::Social sciences::Law
Keywords: Computer crime
Law
Visualization
Stakeholders
Internet
Issue Date: 2018
First Page: 470
Last Page: 475
Volume Title: 2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)
Abstract: Multiple studies and surveys focus on specific cybercrime characteristics or develop classification models that do not adequately address the complexity of this contemporary type of crime. This study proposes a comprehensive approach towards cybercrime interpretation and action recommendation through a proposed framework that provides three separate and complementary views to achieve a comprehensive perspective that leads to actionable recommendations. The framework's view I identifies the features of a cybercrime incident and their corresponding elements generating a textual schema-based description that can accommodate existing and new instances of cybercrime. The second view introduces an up-to-date cybercrime-related offence classification system through consolidation and elaboration of existing approaches and leads to a visual extension of schema-based incident description that depicts the interrelations of the various cybercrime elements towards a particular type of offence. View III identifies and interconnects the relevant stakeholders with preventive and response actions and measures. The proposed framework extends previous published work on the theoretical foundation of this multi-faceted domain, and demonstrates that the necessity of a comprehensive approach towards cybercrime can be actualized through different steps with each one designated towards a different perspective.
URI: https://doi.org/10.1109/CoDIT.2018.8394816
https://ruomo.lib.uom.gr/handle/7000/1696
ISBN: 978-1-5386-5065-3
Other Identifiers: 10.1109/CoDIT.2018.8394816
Appears in Collections:Department of Applied Informatics

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