As digital crimes have risen, so has the need for digital forensics. Numerous state-of-the-art tools have been developed to assist digital investigators conduct proper investigations into digital crimes. However, digital investigations are becoming increasingly complex and time consuming due to the amount of data involved, and digital investigators can find themselves unable to conduct them in an appropriately efficient and effective manner. This situation has prompted the need for new tools capable of handling such large, complex investigations. Data mining is one such potential tool. It is still relatively unexplored from a digital forensics perspective, but the purpose of data mining is to discover new knowledge from data where the dimensionality, complexity or volume of data is prohibitively large for manual analysis. This study assesses the self-organising map (SOM), a neural network model and data mining technique that could potentially offer tremendous benefits to digital forensics. The focus of this study is to demonstrate how the SOM can help digital investigators to make better decisions and conduct the forensic analysis process more efficiently and effectively during a digital investigation. The SOM’s visualisation capabilities can not only be used to reveal interesting patterns, but can also serve as a platform for further, interactive analysis. / Dissertation (MSc (Computer Science))--University of Pretoria, 2007. / Computer Science / unrestricted
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:up/oai:repository.up.ac.za:2263/22996 |
Date | 07 March 2007 |
Creators | Fei, B.K.L. (Bennie Kar Leung) |
Contributors | Eloff, Jan H.P., Venter, Hein S., Olivier, Martin S., benniefei@yahoo.com |
Source Sets | South African National ETD Portal |
Detected Language | English |
Type | Dissertation |
Rights | © 2007, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
Page generated in 0.0019 seconds