Distributed Healthcare Privacy Protection in Emerging Cybersecurity Use of Sensitive Data - Ugochukwu, Okwudili Matthew; Rosa, Renata Lopez; Adenike, Oyedemi Oluyemisi; Rodriguez, Demostenes Zegarra (INFOCOMP Journal of Computer Science, 2025)
The necessity for distributed healthcare information systems have grown in the digital health settings, serving as the foundation for Internet of Things cloud data warehouse repositories management for record federation. The amount of sensitive data that are stored including financial information, medical records, and private communications, as well as the expansion of healthcare distributed systems, raises significant concerns about potential security breaches and exploitation. On the account that sensitive patient data is stored in these distributed healthcare systems, there is need to comply with new cybersecurity requirements. Implementing data-driven technology offers a great chance to make significant improvements in the sector toward better patient and public healthcare use of sensitive data. In this study, the author achieved two essential goals by distinguishing the suggested strategy from all other existing methods of patient healthcare data management. In the beginning, we integrated blockchain technology with a federated learning system to develop a cognitive computing paradigm that enhanced accuracy, making healthcare data warehouse information system fake data injection attacks impossible. In the second approach, the author introduced secured message queuing telemetry transport (MQTT) communication as a gatekeeper strategy to prevent indiscriminate node flooding by allowing selective client admittance by the MQTT broker via the MQTT protocol, which ensured that broker node verification and authentication were harmonized using the Practical Byzantine Fault Tolerance (PBFT) blockchain consensus algorithm.