A Simple WordNet-Ontology Based Email Retrieval System for Digital Forensics

Authors:
Phan Thien Son;Lan Du;Huidong Jin;Olivier Vel;Nianjun Liu;Terry Caelli
Affiliations:
NICTA Canberra Lab, , Canberra, Australia ACT 2601 and RSISE, the Australian National University, Canberra, Australia ACT 0200;NICTA Canberra Lab, , Canberra, Australia ACT 2601 and RSISE, the Australian National University, Canberra, Australia ACT 0200;NICTA Canberra Lab, , Canberra, Australia ACT 2601 and RSISE, the Australian National University, Canberra, Australia ACT 0200;Command, Control, Communications and Intelligence Division, DSTO, Edinburgh, Australia SA 5111;NICTA Canberra Lab, , Canberra, Australia ACT 2601 and RSISE, the Australian National University, Canberra, Australia ACT 0200;NICTA Canberra Lab, , Canberra, Australia ACT 2601 and RSISE, the Australian National University, Canberra, Australia ACT 0200
Venue:
PAISI, PACCF and SOCO '08 Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics
Year:
2008

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Abstract

Because of the high impact of high-tech digital crime upon our society, it is necessary to develop effective Information Retrieval (IR) tools to support digital forensic investigations. In this paper, we propose an IR system for digital forensics that targets emails. Our system incorporates WordNet (i.e. a domain independent ontology for the vocabulary) into an Extended Boolean Model (EBM) by applying query expansion techniques. Structured Boolean queries in Backus-Naur Form (BNF) are utilized to assist investigators in effectively expressing their information requirements. We compare the performance of our system on several email datasets with a traditional Boolean IR system built upon the Lucene keyword-only model. Experimental results show that our system yields a promising improvement in retrieval performance without the requirement of very accurate query keywords to retrieve the most relevant emails.