Harnessing Big data Analytics for Proactive Cyber Threat Intelligence in Health Care Information System

Healthcare organizations are presented with historic cybersecurity challenges as they continue to digitize patient data and medical equipment, producing enormous sets of sensitive information that are sought after by malicious intent. This research explores the potential for the application of big data analytics methods to improve cyber security threat intelligence functions within healthcare database environments. Through the use of machine learning algorithms, real-time data processing, Apache HDFS, Spark and sophisticated pattern recognition techniques, we can create a broad framework for detecting, analysing and counteracting cyber threats to healthcare information systems and databases. The research project has a multi-layered solution that makes use of network traffic analysis, user behaviour analytics, and anomaly detection algorithms to analyse volumes of security logs, audit trails, and system metadata within a large healthcare database infrastructure. The framework proposed here combines structured and unstructured data sources such as firewall logs, intrusion detection system notifications, authentication records, and threat intelligence feeds to provide a comprehensive threat landscape view. The application of predictive analytics models fortified proactive threat hunting ability, enabling security professionals to foretell and avert likely attacks prior to their occurrence. Our research demonstrates that big data analytics could revolutionize healthcare cybersecurity from reactive to predictive, seriously enhancing protection of sensitive patient data and guaranteeing conformity with healthcare data safeguarding regulations like DPDP and IT Act2000. This study adds to the increasing repository of healthcare cybersecurity knowledge and offers an actionable model for organizations that want to exploit big data technologies to achieve better threat intelligence and safeguarding of critical healthcare infrastructure.