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

物联网/边缘设备的部署在整个社会中变得越来越普遍，包括关键的国家基础设施（例如智能能源）。这些设备由于其多样性（许多制造商和协议）以及由于有限的计算资源（低处理能力）而缺乏安全机制，容易受到广泛的网络攻击。虽然最近的进展已经看到机器学习被用于保护这些设备免受网络攻击，但由于这些轻量级设备缺乏计算资源，在设备上部署保护模型往往受到限制。该博士将基于MITRE ATT&CK对抗性威胁建模框架生成威胁，并产生边缘设备社区风险评分的新方法-包括有关减轻控制的建议。这些将在东芝位于布里斯托尔的研究实验室的真实测试平台上进行测试。我们正在寻找一个开放的思想，有创造力的个人加入我们的团队，开发世界级的研究成果与工业应用。您将加入卡迪夫大学ESPRC网络安全分析DTP中心，成为跨学科学生群体的一员，在网络安全背景下研究人工智能的人类和算法方面。

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.