State of Art in Cybersecurity Risk Management with Live AI based Case Study

This session introduces a state-of-the-art approach to cybersecurity risk management in the medical-device lifecycle—bridging ISO 14971, IEC 81001-5-1, AAMI TIR57, and FDA pre- and post-market cybersecurity guidance. Participants will explore how AI-powered analytics can revolutionize the identification, quantification, and continuous monitoring of cybersecurity risks.

The session culminates with a live demonstration of  AI-based CRA (Cyber Risk Assessment) platform, showing how it automates risk identification, evaluation/ scoring (using CVSS v4.0 and exploit likelihood data), maps vulnerabilities and recommends security risk controls—all within an integrated QMS-ready dashboard.

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Learning Objectives​

1. Describe the current regulatory expectations for cybersecurity risk management (FDA, EU MDR/IVDR Annex I 17.2, and IEC 81001-5-1).

2. Differentiate between traditional hazard-based risk frameworks and modern cyber-threat-driven models (STRIDE, DREAD, and CVSS).

3. Understand how AI and natural-language processing can assist in Cybersecurity Risk Management Program

4. Apply the concept of an AI-powered Cyber Risk Assessment tool to streamline documentation and make it more efficient, accurate and holistic.