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Computer-Aided Writeprint Modelling for Cybercrime Investigations


Computer-Aided Writeprint Modelling for Cybercrime Investigations

Schmid, Michael (2012) Computer-Aided Writeprint Modelling for Cybercrime Investigations. Masters thesis, Concordia University.

Text (application/pdf)
Schmid_MASc_F2012.pdf - Accepted Version


E-mail has become the most common way to communicate on the Internet, but e-mail security and privacy mechanisms are still lacking. This has proven to be a very valuable characteristic for criminals, who can easily take advantage of e-mail’s various weaknesses to remain anonymous. Consequently, cybercrime investigators need to rely on computer-aided writeprint modelling methods and tools to identify the real author of malicious e- mails with transformed semantic content. In this paper, we propose a customized version of associative classification, a well-known data mining method, as well as a Support Count method, to address the authorship attribution problem. Experimental results on real-life data suggest that our proposed algorithms can achieve good classification accuracy on the e-mail author attribution problem through the use of writeprint modelling.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Concordia Institute for Information Systems Engineering
Item Type:Thesis (Masters)
Authors:Schmid, Michael
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Information Systems Security
Date:10 April 2012
Thesis Supervisor(s):Fung, Benjamin
ID Code:974093
Deposited On:25 Oct 2012 14:39
Last Modified:18 Jan 2018 17:37
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