Predictive textmining for cyber and digitized crime in police

Criminology and victimology / Offender characteristics

Predictive textmining for cyber and digitized crime in police

(full text only available in Dutch)

Summary

In this study, a machine learning (ML) model was developed to classify police records in the Basis Voorziening Handhaving (BVH; the policy database that contains information on incidents reported to the police) that relate to cyber- or digitized crime. With that ML-model the extent of online crime in the BVH registration of 2016 is estimated. The background characteristics of linked suspects in these registrations of cyber and digitized crime have also been described. The research focused on registrations of three types of cybercrime (hacking, ransomware and DDoS attacks) and five types of digitized crime (online threats, stalking, online libel / slander / insult, online identity fraud and online buying and selling fraud).

Publication data

Author(s):
Tollenaar, N., Rokven, J., Macro, D., Beerthuizen, M., Laan, A.M. van der
Organization(s):
WODC
Place of publication:
The Hague
Publisher:
WODC
Year of publication:
2019
Series:
Cahiers 2019-02

Order information

Address:
Voor een electronische versie - zie: bijlagen (rechtsboven) (only available as pdf)