Advanced device-to-device technology for secure internet-of-things
Principal Supervisor: Dr. Youngwook Ko
Second Supervisor: Prof. William Scanlon
+ Project Description
Internet of Things (IoT) market will reach $1.7 trillion by 2020, growing to 75 billion connected devices in 5 years. Within IoT, short-range device-to-device (D2D) communications promise to interconnect diverse devices with a significant increase in data traffics (a 1000-fold increase by 2020). Particularly, the UK government has emphasised the great potential of IoT in energy sector (e.g., smart grids) to deliver on its opportunities.
The UK’s energy system is evolving. Heating accounts for 79% of UK domestic energy use. By 2020, up to 53 million electricity and gas smart meters in homes and small business will be connected via, e.g., SUNs and 802.15.4g . On the other hand, smart meter (SM) relies increasingly on heterogeneous, sophisticated new IoT sensing technologies (e.g., air, humidity, water, heating, light, noise) allied to intelligent interpretation to building energy management. Therefore, there is a strong need to process diverse data (e.g., energy demands, energy usage patterns, energy leakage, energy types) autonomously at source, either to considerably reduce the amount of data being transferred between the SM and distributed sensors. In addition, heavily dense presence of random devices in the IoT will cause significant impact on D2D’s reliability and secrecy at the physical device level (not at the computational level). However, the state-of-the-art D2D performs very far from its best.
In this context, this PhD programme of study will investigate new D2D techniques improving the level of wireless secrecy in IoT (Secure-IoT). In presence of dense eavesdropper devices, we will develop in the stochastic geometry framework a secure pre-processor that translates challenges of new D2D waveform structure into opportunities of anti-interception, over large bandwidth. It will focus on physical layer D2D communications and in particular optimally leveraging the physical layer properties of wireless channels in dense D2D environment. This will ensure secrecy of IoT at the physical layer which is highly desired in future IoT networks (e.g., miniature sensing + IoT, vehicular-to-grid, smart home).
+ How to Apply
Applicants should apply electronically through the Queen’s online application portal at: https://dap.qub.ac.uk/portal/
+ Contact Details
|Supervisor Name:||Dr Youngwook Ko|
Queens University of Belfast
+44 (0)28 9097 1772