Machine Learning (ML) and Deep Learning (DL) are playing an increasingly critical role in enhancing security and privacy within the Internet of Medical Things (IoMT). As IoMT environments face diverse threats and complex attack vectors, understanding their unique security requirements is essential. This paper explores the key challenges related to IoMT security, presents various ML and DL methods applied in this context, and reviews existing security solutions. It also identifies open research problems that must be addressed to strengthen the resilience of IoMT systems.
Internet of Medical Things: Enhancing Security Through Machine Learning / Lazzeretti, R.. - (2026), pp. 185-204. (14th Italian Forum of Ambient Assisted Living, ForItAAL 2025 Rome; Italy ) [10.1007/978-3-032-11050-3_12].
Internet of Medical Things: Enhancing Security Through Machine Learning
Riccardo Lazzeretti
2026
Abstract
Machine Learning (ML) and Deep Learning (DL) are playing an increasingly critical role in enhancing security and privacy within the Internet of Medical Things (IoMT). As IoMT environments face diverse threats and complex attack vectors, understanding their unique security requirements is essential. This paper explores the key challenges related to IoMT security, presents various ML and DL methods applied in this context, and reviews existing security solutions. It also identifies open research problems that must be addressed to strengthen the resilience of IoMT systems.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


