Visible to the public Biblio

Filters: Author is Hancke, G. P.  [Clear All Filters]
2017-12-20
Pritchard, S. W., Hancke, G. P., Abu-Mahfouz, A. M..  2017.  Security in software-defined wireless sensor networks: Threats, challenges and potential solutions. 2017 IEEE 15th International Conference on Industrial Informatics (INDIN). :168–173.
A Software-Defined Wireless Sensor Network (SD-WSN) is a recently developed model which is expected to play a large role not only in the development of the Internet of Things (IoT) paradigm but also as a platform for other applications such as smart water management. This model makes use of a Software-Defined Networking (SDN) approach to manage a Wireless Sensor Network (WSN) in order to solve most of the inherent issues surrounding WSNs. One of the most important aspects of any network, is security. This is an area that has received little attention within the development of SDWSNs, as most research addresses security concerns within SDN and WSNs independently. There is a need for research into the security of SDWSN. Some concepts from both SDN and WSN security can be adjusted to suit the SDWSN model while others cannot. Further research is needed into consolidating SDN and WSN security measures to consider security in SDWSN. Threats, challenges and potential solutions to securing SDWSN are presented by considering both the WSN and SDN paradigms.
2017-03-08
Pienaar, J. P., Fisher, R. M., Hancke, G. P..  2015.  Smartphone: The key to your connected smart home. 2015 IEEE 13th International Conference on Industrial Informatics (INDIN). :999–1004.

Automation systems are gaining popularity around the world. The use of these powerful technologies for home security has been proposed and some systems have been developed. Other implementations see the user taking a central role in providing and receiving updates to the system. We propose a system making use of an Android based smartphone as the user control point. Our Android application allows for dual factor (facial and secret pin) based authentication in order to protect the privacy of the user. The system successfully implements facial recognition on the limited resources of a smartphone by making use of the Eigenfaces algorithm. The system we created was designed for home automation but makes use of technologies that allow it to be applied within any environment. This opens the possibility for more research into dual factor authentication and the architecture of our system provides a blue print for the implementation of home based automation systems. This system with minimal modifications can be applied within an industrial application.