Towards AI-enabled Cyber Threat Assessment in the Health Sector

TL;DR

This paper proposes an AI-enabled platform for assessing cyber threats in healthcare, aiming to improve security decision-making amid increasing digitalization and complex infrastructure.

Contribution

It introduces a novel architecture for an AI-based threat assessment platform tailored for the healthcare sector, integrating data collection, analysis, and risk scoring.

Findings

Designed platform architecture for healthcare cybersecurity

Identified key information sources for threat assessment

Explored AI methods for data analysis and risk scoring

Abstract

Cyber attacks on the healthcare industry can have tremendous consequences and the attack surface expands continuously. In order to handle the steadily rising workload, an expanding amount of analog processes in healthcare institutions is digitized. Despite regulations becoming stricter, not all existing infrastructure is sufficiently protected against cyber attacks. With an increasing number of devices and digital processes, the system and network landscape becomes more complex and harder to manage and therefore also more difficult to protect. The aim of this project is to introduce an AI-enabled platform that collects security relevant information from the outside of a health organization, analyzes it, delivers a risk score and supports decision makers in healthcare institutions to optimize investment choices for security measures. Therefore, an architecture of such a platform is designed, relevant information sources are identified, and AI methods for relevant data collection, selection, and risk scoring are explored.