Testing a hybrid risk assessment model: Predicting CSAM offender risk from digital forensic artifacts

Area of Science:

• Digital Forensics
• Cybercrime Analysis
• Risk Assessment

Background:

• Formalized hybrid risk assessment models are proposed, integrating online child sex abuse risk measures with digital forensics.
• Existing risk measures need enhancement with objective digital evidence.

Purpose of the Study:

• To conduct a feasibility study for a hybrid risk assessment model.
• Identify high-level digital forensic artifacts as potential indicators of risk.
• Focus on Child Pornography Offender Risk Tool (CPORT) Items 5, 6, and 7.

Main Methods:

• Seven closed cases involving male offenders over 18 and child sexual abuse material (CSAM) offenses were analyzed.
• Digital forensic artifacts examined included pornography collection and evidence of online networking/grooming.
• Statistical analysis predicted offender type (CSAM-only vs. dual) and risk level.

Main Results:

• The hybrid model achieved 85.7% accuracy (6 out of 7 cases).
• Findings aligned with CPORT risk indicators.
• The analysis highlighted the significance of app artifacts for contextual understanding.

Conclusions:

• A hybrid risk assessment model integrating digital forensics is feasible.
• Analyzing application artifacts provides essential context for risk assessment.
• Further research is recommended to refine the model and address limitations.