<p>Every year thousands of new digital consumer device models come on the market. These devices include video cameras, photo cameras, computers, mobile phones and a multitude of different combinations. Most of these devices have the ability to store information in one form or another. This is a problem for law enforcement agencies as they need access to all these new kinds of devices and the information on them in investigations. Forensic analysis of electronic and digital equipment has become much more complex lately because of the sheer number of new devices and their increasing internal technological sophistication. This thesis tries to help the situation by reverse engineering a Qtek S110 device. More specifically we analyze how the storage system of this device, called the object store, is implemented on the devices operating system, Windows Mobile. We hope to figure out how the device stores user data and what happens to this data when it is "deleted". We further try to define a generalized methodology for such forensic analysis of unknown digital devices. The methodology takes into account that such analysis will have to be performed by teams of reverse-engineers more than single individuals. Based on prior external research we constructed and tested the methodology successfully. We were able to figure our more or less entirely the object stores internal workings and constructed a software tool called BlobExtractor that can extract data, including "deleted", from the device without using the operating system API. The main reverse engineering strategies utilized was black box testing and disassembly. We believe our results can be the basis for future advanced recovery tools for Windows Mobile devices and that our generalized reverse engineering methodology can be utilized on many kinds of unknown digital devices.</p>
| Identifer | oai:union.ndltd.org:UPSALLA/oai:DiVA.org:ntnu-10060 |
| Date | January 2006 |
| Creators | Eide, Jarle, Olsen, Jan Ove Skogheim |
| Publisher | Norges Teknisk-Naturvitenskaplige Universitet, Institutt for datateknikk og informasjonsvitenskap, Norges Teknisk-Naturvitenskaplige Universitet, Institutt for datateknikk og informasjonsvitenskap, Institutt for telematikk |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, text |
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