PhD Dissertation: A Defense-in-Depth Framework for IoT/CPS Ransomware Attacks Protection

The proliferation of Internet of Things (IoT) devices has enhanced connectivity and productivity across various industries. However, this growth also brings security challenges, particularly as advanced ransomware increasingly targets IoT devices. While traditional ransomware usually targets data confidentiality, IoT ransomware can impact a device’s functionality and the confidentiality of the data stored. This paper summarizes three solutions designed to detect ransomware threats in IoT systems based on the defense-in-depth principle: L-IDS, a lightweight hardware-assisted intrusion detection system (IDS) that integrates machine learning (ML) algorithms and advanced anomaly detection techniques; RansomSentry, a lightweight, hardware-level monitoring solution to detect ransomware activity in IoT environment; and a cross-layer security solution focused on improving overall security performance while using minimum IoT device resources. This approach aims to provide layered, scalable, efficient, and robust security for IoT systems, effectively mitigating the evolving ransomware threat without compromising performance.