Digital forensic intelligence for illicit drug analysis in forensic investigations

Area of Science:

• Forensic Science
• Criminology
• Information Science

Background:

• Forensic intelligence is crucial for effective illicit drug profiling and law enforcement.
• Current methods may lack integrated approaches for analyzing diverse data sources.
• Recognizing crime developments and adjusting law enforcement actions requires robust intelligence.

Purpose of the Study:

• To propose a novel framework for Digital Forensic Drug Intelligence (DFDI).
• To fuse digital forensic data with drug profiling data for enhanced intelligence.
• To support law enforcement in understanding and combating illicit drug trafficking.

Main Methods:

• Development of a framework integrating digital forensics and drug profiling.
• Intelligent cycles involving targeted and iterative evidence collection from diverse sources.
• Analysis of combined digital data from seized devices and drug profiling information.

Main Results:

• The proposed DFDI framework enables the generation of valuable intelligence on drug trafficking.
• Fusion of data allows for better identification of drug trafficking routes and manufacturing.
• Centralized databases can store findings, hypotheses, and recommendations for decision-making.

Conclusions:

• The DFDI framework offers a novel approach to illicit drug profiling.
• It enhances law enforcement's understanding of drug profiling, trafficking, and distribution.
• This integrated intelligence approach can lead to more informed and effective law enforcement strategies.