Quantum-driven predictive cybersecurity framework for safeguarding Electronic Health Records (EHR) and enhancing patient data privacy in healthcare systems

Cyberattacks threaten the safety and security of patient data and system integrity, and these have been a major problem healthcare faces in recent times. Their main target is the Electronic Health Records (EHR) of the industry. These cyberattacks come with serious consequences such as disruption of operations, ransomware infections and data breaches to mention a few [1]. This paper explains how quantum-driven predictive cybersecurity framework can secure EHR systems through the use of quantum computing and machine learning. The application of quantum algorithms such as Quantum Support Vector Machines (QSVM) and Grover’s Search helps in detecting, preventing and predicting cyber threats [2, 3]. The paper also focuses on end-to-end methodology, real-world case scenarios, traditional models, comparative analysis and implementable recommendations.