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Abstract
This dissertation aims to conduct a comprehensive study on various aspects of Electromagnetic (EM) side-channel vulnerabilities, with a particular focus on Hardware Trojans (HT) detection and intentional EM interference attacks. The primary objective is to enhance the security and efficiency of modern computing systems both as hardware and software. The study will explore deep learning techniques for detecting hardware Trojans through EM side-channel analysis, identifying specific EM patterns that indicate the presence of malicious modifications. It will also involve the development of programmable on-chip EM sensor arrays for real-time monitoring and analysis of EM emissions, and investigate how conductive and radiated EM interference can impact various cyber-physical systems, including integrated circuits (IC) and also power electronic systems.
In addition to these primary goals, the research will expand to address new findings closely related with these innovations. These extensions include integrating on-chip sensors with EM backscattering techniques to improve HT detection accuracy, and developing a cross-layer EM fault injection assessment framework to ensure robust defense mechanisms. Furthermore, the study will examine how intentional electromagnetic interference can manipulate wireless charging systems, identifying vulnerabilities and proposing mitigation strategies. The findings from this research are expected to significantly contribute to hardware security, providing a comprehensive understanding of EM side-channel phenomena and practical solutions to mitigate risks.