To develop an anomaly detection system using artificial intelligence and machine learning algorithms to identify security threats in integrated hospital network systems.
To implement predictive security measures based on the identified anomalies to prevent potential cybersecurity breaches and ensure the confidentiality and integrity of sensitive patient data.
To assess the effectiveness of the proposed system in enhancing the overall cybersecurity posture of hospital network systems and improving patient data protection.
Conduct a literature review on existing anomaly detection and predictive security solutions in healthcare IT systems.
Design and develop an AI-powered anomaly detection model tailored for integrated hospital network systems.
Implement predictive security measures based on the identified anomalies and evaluate their effectiveness in preventing potential security threats.
Analyze and document the results of the implementation, including any improvements in cybersecurity posture and patient data protection.
Present the findings of the research project in a comprehensive report and a professional presentation.
