Organization
Australian Institute of Criminology
Description
Report by the Australian Institute of Criminology that analyses child sexual abuse (CSA) and financial transactions through machine learning in order to identify characteristics of offenders who live stream CSA in high volumes. The analysis showed that factors such as frequency and monetary value are important and have implications for identifying these crimes among financial transaction data. Furthermore, offenders did not appear to have engaged in violent offending, but rather had a criminal history of low-harm offences.
File
Link
https://search.informit.org/doi/abs/10.3316/agispt.20211101056192
Tags
Financial transactionsArtificial intelligenceSupervised learningMachine learningCriminal investigationChild Sexual Abuse Material (CSAM)
Type
Research (peer reviewed)
Year
2021
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Singidunum University
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Unicef
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Child-focusedPost-traumatic stress (PTS)Post-crime efforts
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