AI Driven IoT Healthcare Devices Security Vulnerability Management
Pragya Bajpayi, Smita Sharma, Madhu Sharma Gaur
Abstract
In the modern healthcare ecosystem, emerging technologies, Internet of Things(IoT) medical devices playing major role for providing seamless and remote clinical care, disease diagnosis, patient monitoring and many more healthcare services. Wireless, seamless sensor devices and underlying infrastructure creates the IoT ecosystem. An IoT device identification and vital healthcare data collection are the most important where vulnerability management and security is a critical aspect of IoT security Against a number of vulnerabilities, attacks and cyber threats, a proactive approach needs to be builds for Internet of Things medical devices security resilience. In the current fast moving digital transformation, integrating Artificial Intelligence (AI)-driven safety measures into IoT enabled healthcare applications represents a significant advance in building a secure and trustworthy healthcare system. The AI system can identify ordinary patterns of behavior and swiftly recognize any deviations suggestive of a possible security risk or unauthorized access through the continuous analysis of data flows from networked sensor devices. In order to enhance the security of IoT medical devices, we explore security vulnerabilities in IoT enabled healthcare applications and propose an Artificial Intelligence (AI) driven approach for IoT Device level vulnerabilities management life cycle for known and unknown vulnerability detection and protection based on zero tolerance and zero-trust model. The aim of this work is to strengthen the healthcare data vulnerability management strategy through zero-trust based strategy and AI-driven automated IoT devices security vulnerabilities management and risk assessment for an application on managed or unmanaged clinical and diagnosis operational services.