  Managing access between large numbers of distributed medical devices has
become a crucial aspect of modern healthcare systems, enabling the
establishment of smart hospitals and telehealth infrastructure. However, as
telehealth technology continues to evolve and Internet of Things (IoT) devices
become more widely used, they are also becoming increasingly exposed to various
types of vulnerabilities and medical errors. In healthcare information systems,
about 90\% of vulnerabilities emerged from misuse cases and human errors. As a
result, there is a need for additional research and development of security
tools to prevent such attacks. This article proposes a zero-trust-based
context-aware framework for managing access to the main components of the cloud
ecosystem, including users, devices and output data. The main goal and benefit
of the proposed framework is to build a scoring system to prevent or alleviate
misuse cases while using distributed medical devices in cloud-based healthcare
information systems. The framework has two main scoring schemas to maintain the
chain of trust. First, it proposes a critical trust score based on cloud-native
micro-services of authentication, encryption, logging, and authorizations.
Second, creating a bond trust scoring to assess the real-time semantic and
syntactic analysis of attributes stored in a healthcare information system. The
analysis is based on a pre-trained machine learning model to generate the
semantic and syntactic scores. The framework also takes into account regulatory
compliance and user consent to create a scoring system. The advantage of this
method is that it is applicable to any language and adapts to all attributes as
it relies on a language model, not just a set of predefined and limited
attributes. The results show a high F1 score of 93.5%, which proves that it is
valid for detecting misuse cases.
