Computers and the internet have become an integral part of our lives. People have grown
accustomed to feeling constantly connected to the outside world, and in the past couple of
decades online social networks and three-dimensional online virtual worlds have gained
great popularity. In addition to social connections, virtual worlds (such as Second Life,
a popular virtual world) offer their users opportunities for both work and play, and let
them take part in things that might have been impossible in real life. However, the human
factor plays a big role in the formation of the virtual community. The feeling of false
anonymity online might lead to a feeling of freedom from any laws that govern the real
world, and possibly facilitate offensive behaviour. The problem addressed by this study is the need to determine whether digital forensic techniques can be applied to an incident inside the Second Life environment (i.e. offensive behaviour between avatars, while logged in to Second Life), as well as to find possible sources of evidence accessible via the standard Second Life viewer. The former also requires a classification of various offenses committed in Second Life, in order to determine which actions are to be regarded as offences, and whether these actions occur inside or outside of the Second Life environment. In this dissertation the author’s own classification of various real-life offences is provided, together with a mapping of these offences to their alternatives in Second Life. Second Life is analysed and explored from a forensic perspective. A new digital forensic process model, derived from various existing models in the literature, has been developed by the author for this study. The model is designed to accommodate for the specifics of a virtual world environment. An exploratory experiment has been undertaken by the author in order to investigate how inexperienced users perceived Second Life, as well as how they reacted to attacks from other users, to identify the possible sources of evidence, and suggest possible digital forensic techniques based on the gathered data. / Dissertation (MSc)--University of Pretoria, 2015. / Computer Science / MSc / Unrestricted
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:up/oai:repository.up.ac.za:2263/44263 |
Date | January 2015 |
Creators | Rakitianskaia, A.S. (Anastassia Sergeevna) |
Contributors | Olivier, Martin S., Cooper, Antony K. |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Type | Dissertation |
Rights | © 2015 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. |
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