Relevance Feedback Optimisation for Digital Forensic Investigations

Hanadi Al Suwaidi

Programme: PhD Computer Science

Year of Graduation: 2019

Supervisor: Prof. Sherief Abdallah


Relevance Feedback Optimisation for Digital Forensic Investigations


Digital forensics deals with the use of tools and techniques to preserve, identify, extract, document, and interpret any data stored or transmitted using a digital system. It is usually used to help support or refute a theory, for the occurrence of an offence or crime, or it might indicate intent or alibi.

The work presented in this thesis can be seen as a step forward into enhancing digital forensics investigations by optimising the investigator’s relevancy feedback. The study proposes a framework that integrates different text processing and mining techniques to assist the examiner to reach useful information faster. The framework has been implemented and evaluated using a real world crime dataset of Arabic text. A Proof-of-Concept implementation was evaluated by experienced senior digital forensics examiners. The results showed a good improvement in the average recall-precision rates and a reduction of the required time to complete the tasks by 53% over the time spent using traditional tools.

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