Schmid, Michael (2012) Computer-Aided Writeprint Modelling for Cybercrime Investigations. Masters thesis, Concordia University.
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 > Faculty of Engineering and Computer Science > Concordia Institute for Information Systems Engineering|
|Item Type:||Thesis (Masters)|
|Degree Name:||M.A. Sc.|
|Program:||Information Systems Security|
|Date:||10 April 2012|
|Thesis Supervisor(s):||Fung, Benjamin|
|Deposited By:||MICHAEL SCHMID|
|Deposited On:||25 Oct 2012 14:39|
|Last Modified:||05 Nov 2016 02:27|
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