EPSRC DTP studentship in Cyber Security Analytics: Machine learning threat detection for low complexity edge deployment: threats, risks and mitigation

The deployment of IoT/edge devices is becoming increasing prevalent across society, including in critical national infrastructure (e.g. smart energy). These devices are vulnerable to a wide range of cyber attacks due to their diversity (many manufacturers and protocols) and lack of security mechanisms due to limited compute resource (low processing power). While recent advancements have seen machine learning used to protect such devices from cyber attacks, the deployment of protective models on the devices themselves is often limited due to the lack of compute resource on these lightweight devices.

This PhD will generate threats based around the MITRE ATT&CK adversarial threat modelling framework, and produce new methods for edge-device community risk scoring - including suggestions around mitigating controls. These will be tested in a real-world testbed at Toshiba's research labs in Bristol. We are seeking an open minded, creative individual to join the team and develop world class research outcomes with industrial applications. You will join the ESPRC DTP Hub in Cyber Security Analytics at Cardiff University, becoming part of an interdisciplinary cohort of students studying the human and algorithmic aspects of AI in the context of cybersecurity.