AI-ASSISTED SECURITY ORCHESTRATION IN HEALTHCARE INCIDENT RESPONSE
Keywords:
AI-SOAR, Security Orchestration, Automation, electronic health records (EHRs), patient safety, malware, ransomware, targeted phishing attacks, security information and event management system (SIEM),,,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.
