A Secure Authentication Technique in Internet of Medical Things through Machine Learning
This addresses security and privacy risks for patients in healthcare IoT systems, but appears incremental as it builds on existing authentication methods.
The paper tackles security threats in the Internet of Medical Things (IoMT) by proposing a new machine learning-based authentication approach to enhance security levels, though no concrete results or numbers are provided.
The rapid growth of the Internet of Things technology in healthcare domain led to the appearance of many security threats and risks. It became very challenging to provide full protection with the expansion in using sensor objects in medical field, this led to the Internet of Medical Things definition, the security part in IoMT poses a perilous problem that keeps growing, because of the data sensitivity and critical information. The lack of providing a secure environment in IoMT may lead to patients privacy issues, not only leaving the data privacy of the patients at risk but also their lives can be in danger. In this paper, we provide a discussion on both definition and architecture of the Internet of Medical Things and Propose a new authentication approach through machine learning, to enhance the security level.