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.
2026
14th Italian Forum of Ambient Assisted Living, ForItAAL 2025
Internet of medical things; Privacy; Security
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
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].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1770934
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