Explore how Software Defined Radios expose & detect radio‑frequency vulnerabilities across 5G, autonomous systems & critical infrastructure

This event invites participants from all disciplines and backgrounds to come together, fostering interdisciplinary connections and discussions.

Talk Title: Software Defined Radios: RF Enabled Cyber Vulnerability Exposure and Early Warning

Often when Cyber threats are considered, fixed (or wired) Internet connections are the assumed way that a target device is accessed. However, Radio Frequency (RF) links are becoming more prevalent in connected systems, from 5G to driverless cars and even control systems for Critical National Infrastructure. There is a growing need to consider RF links when securing networks and identifying potential vulnerabilities. Software Defined Radios (SDRs) expose vulnerabilities by providing a viable means to access or even deny access to these links. In this seminar the term SDR will be defined and the capabilities of open-source software in conjunction with low cost, easily available devices on the market today, will be demonstrated through a practical implementation. Academic literature will highlight vulnerabilities to capabilities from Global Navigation Satellite Systems (GNSS) position and timing information to drone delivery services and remote keyless systems. However, SDRs can also provide early warning of unwanted RF signals and, in conjunction with machine learning techniques, can classify those signals with high accuracy. Hence, the seminar will also explore the use of SDRs for the detection and classification of threats.

Speaker Biography:

Carolyn J. Swinney received a B.Eng.(hons.) degree (first class) in 2007 and a M.Sc.(dist.) in Electronics Engineering from the University of Essex, Colchester, UK in 2013. She graduated as a Communications and Electronics Engineering Officer in the Royal Air Force in 2014. She is currently a student of the Advanced Command and Staff College at the UK Defence Academy and an Executive Fellow with the University of Essex. Her main research interests are signal processing, unmanned aerial vehicles, neural networks, machine learning and cyber security.