AI-ASSISTED SECURITY ORCHESTRATION IN HEALTHCARE INCIDENT RESPONSE

Abstract

This paper discusses how Security Orchestration, Automation, and Response (SOAR) systems with the help of Artificial Intelligence (AI) can be used to improve incident response in healthcare settings. With growing cases of advanced cyberattacks on patient health records and the internet of medical devices, manual response systems are failing to address the challenge among healthcare facilities. Integration of SOAR and AI technologies, including machine learning and natural language processing, can help automate the threat detection process, simplify the response process, and eliminate analyst burnout. This study reviews several studies to measure the AI-SOAR models, point out effective case studies, and determine the practical advantages of healthcare cybersecurity. Moreover, it specifies the main challenges, i.e. adversarial attacks, integration issues, and ethical issues, and offers such effective solutions as adversarial training, standard APIs, and human-in-the-loop systems. The results imply that, although AI-SOAR systems have a considerable positive impact on the resilience of healthcare cybersecurity, interoperability, explainability, and strong governance should be regarded as key requirements for successful implementation.

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