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Mining criminal networks from unstructured text documents

Title:

Mining criminal networks from unstructured text documents

Al-Zaidy, Rabeah, Fung, Benjamin C.M., Youssef, Amr M. and Fortin, Francis (2012) Mining criminal networks from unstructured text documents. Digital Investigation, 8 (3-4). pp. 147-160. ISSN 17422876

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Official URL: http://dx.doi.org/10.1016/j.diin.2011.12.001

Abstract

Digital data collected for forensics analysis often contain valuable information about the suspects’ social networks. However, most collected records are in the form of unstructured textual data, such as e-mails, chat messages, and text documents. An investigator often has to manually extract the useful information from the text and then enter the important pieces into a structured database for further investigation by using various criminal network analysis tools. Obviously, this information extraction process is tedious and error-prone. Moreover, the quality of the analysis varies by the experience and expertise of the investigator. In this paper, we propose a systematic method to discover criminal networks from a collection of text documents obtained from a suspect’s machine, extract useful information for investigation, and then visualize the suspect’s criminal network. Furthermore, we present a hypothesis generation approach to identify potential indirect relationships among the members in the identified networks. We evaluated the effectiveness and performance of the method on a real-life cybercrimine case and some other datasets. The proposed method, together with the implemented software tool, has received positive feedback from the digital forensics team of a law enforcement unit in Canada.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Concordia Institute for Information Systems Engineering
Item Type:Article
Refereed:Yes
Authors:Al-Zaidy, Rabeah and Fung, Benjamin C.M. and Youssef, Amr M. and Fortin, Francis
Journal or Publication:Digital Investigation
Date:2012
Digital Object Identifier (DOI):10.1016/j.diin.2011.12.001
ID Code:974920
Deposited By: ANDREA MURRAY
Deposited On:30 Oct 2012 16:02
Last Modified:18 Jan 2018 17:39
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