Internet of Medical Things (IoMT) Inventory
Description
Automated categorization of medical devices based on MAC Address, installed software, network activity, etc.: the previous method was to schedule down time with clinical staff to manually verify if patches and vulnerabilities were installed and if not, manually install them.
Detailed example
AI Use Case has AI via ML collect and organize information, then a person acts on it. A person generates a report and AI then collects and organizes the information in a format the user requested. The output will allow the user to see what systems have and have not been patched, are properly configured, etc.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
b) Pilot – The use case has been deployed in a limited test or pilot capacity.
Expected benefit
Used to identify devices and report operating system (OS) updates and vulnerability patches that have been installed to meet agency's NIST requirements. This will result in savings in personnel time (work hours) and reduce the downtime of a medical device.
Controls / human review
ATO: Not reported; PIA: Not published