AI and Multi-Factor Authentication (MFA) in IAM for Healthcare

Abstract

In the rapidly evolving landscape of healthcare cybersecurity, the integration of Artificial Intelligence (AI) into Multi-Factor Authentication (MFA) systems presents a promising solution to bolster Identity and Access Management (IAM) security. This paper explores how AI enhances MFA by improving user verification processes, reducing the risk of unauthorized access, and mitigating the impact of increasingly sophisticated cyber threats. We investigate various AI techniques, including machine learning algorithms and behavioral biometrics, that enable realtime threat detection and adaptive authentication mechanisms. Through a comprehensive analysis of existing literature and case studies, we demonstrate the effectiveness of AI-driven MFA systems in healthcare settings, highlighting their role in ensuring data integrity and compliance with regulatory standards. Furthermore, we address the challenges and limitations associated with implementing AI in MFA, providing recommendations for healthcare organizations to optimize their IAM strategies. This study underscores the critical need for continuous innovation in cybersecurity measures as healthcare organizations strive to protect sensitive patient information from emerging threats.