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2021 | OriginalPaper | Buchkapitel

Text Mining for Cybercrime in Registrations of the Dutch Police

verfasst von : André M. van der Laan, Nikolaj Tollenaar

Erschienen in: Cybercrime in Context

Verlag: Springer International Publishing

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Abstract

Aim: Surveys mention substantial rates of cybercrime victimization. However, little is known about the number of police registrations that refer to cybercrime. The aim of this study was to estimate the number of police registrations referring to cybercrime in the Netherlands based on text fields within the police registration system. We focused on cyber-dependent crime (hacking, ransomware and DDoS attacks), as well as on cyber-enabled crime (online threats, stalking, libel, identity fraud and buying and selling fraud). Method: A random sample of Dutch police registrations from 2016 (n = 100.000) was selected, to estimate the number of cybercrime referrals. A machine-learning classifier was developed using text, in order to classify police registrations as referring to a type of cybercrime. Results: In 2016, between 0.10% and 0.62% of all registrations refer to cyber-dependent crime and between 3.33% and 7.41% were related to cyber-enabled crime. These estimates fall in between the rate of police-reported victimization of cybercrime and the number of cybercrimes based on the police’s uniform crime registration. Conclusion: Estimates of the rate of police-registered cybercrime based on textual fields of the police registrations were found to be relatively low but in absolute numbers substantial.

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Vorheriges Kapitel Cybercrime Reporting Behaviors Among Small- and Medium-Sized Enterprises in the Netherlands

Nächstes Kapitel Law Enforcement and Disruption of Offline and Online Activities: A Review of Contemporary Challenges

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Titel: Text Mining for Cybercrime in Registrations of the Dutch Police
verfasst von: André M. van der Laan
Nikolaj Tollenaar
Verlag: Springer International Publishing
Buch: Cybercrime in Context
Print ISBN: 978-3-030-60526-1

Electronic ISBN: 978-3-030-60527-8

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-3-030-60527-8_18

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