Date of Award
Doctor of Philosophy
School of Science
Professor Craig Valli
Professor Andrew Woodward
Portable and wearable computing devices such as smart watches, navigation units, mobile phones, and tablet computers commonly ship with Global Navigation Satellite System (GNSS) supported locational awareness. Locational functionality is no longer limited to navigation specific devices such as satellite navigation devices and location tracking systems. Instead the use of these technologies has extended to become secondary functionality on many devices, including mobile phones, cameras, portable computers, and video game consoles. The increase in use of location aware technology is of use to forensic investigators as it has the potential to provide historic locational information. The evidentiary value of these devices to forensic investigators is currently limited due to the lack of available forensic tools and published methods to properly acquire and analyse these data sources. This research addresses this issue through the synthesis of common processes for the development of forensic procedure to acquire and interpret historic locational data from embedded, locationally aware devices.
The research undertaken provides a framework for the generation of forensic procedure to enable the forensic extraction of historical locational data. The framework is device agnostic, relying instead on differential analysis and structured testing to produce a validated method for the extraction of locational history. This framework was evaluated against five devices, selected on a basis of market penetration, availability and a stage
The examination of the framework took place in a laboratory developed specifically for the research. This laboratory replicates all identified sources of location data for the devices selected. In this case the laboratory is able to simulate cellular (2G and 3G), GNSS (NAVSTAR and GLONASS), and Wi-Fi locationing services. The laboratory is a closed-sky facility, meaning that the laboratory is contained within a faraday cage and all signals are produced and broadcast internally.
Each selected device was run through a series of simulations. These simulations involved the broadcast of signals, replicating the travel of a specific path. Control data was established through the use of appropriate data recording systems, for each of the simulated location signals. On completion of the simulation, each device was forensically acquired and analysed in accordance with the proposed framework.
For each experiment carried out against the five devices, the control and experimental data were compared. In this examination any divergence less than those expected for GNSS were ignored. Any divergence greater than this was examined to establish cause.
Predictable divergence was accepted and non-predictable divergence would have been noted as a limitation. In all instances where data was recovered, all divergences were found to be predictable.
Post analysis, the research found that the proposed framework was successful in producing locational forensic procedure in a non-device specific manner. This success was confirmed for all the devices tested.
Hannay, P. (2017). A non-device specific framework for the development of forensic locational data analysis procedure for consumer grade small and embedded devices. https://ro.ecu.edu.au/theses/2026