Cybersecurity Issues on E-Healthcare Cloud Data Warehouse System: Blockchain-Based Federated Learning Approach

Esegbona-Isikeh, Ogheneruona Maria; Oriakhi, Victor Nosakhare; Falebita, Oluwatosin Samuel; Esseme, Alain Claude Bah; Nwaiku, Morgan; Oforgu, Chukwuka Michael; Matthew, Ugochukwu Okwudili; Onyenagubom, Victor Onuchi

Abstract

In order to detect denial-of-service (DoS) and distributed denial of service (DDoS) intrusions on the organization's e-healthcare data warehouse infrastructure, the authors of this study proposed a computing framework that combines a federated learning system based on blockchain technology. A Message Queuing Telemetry Transport (MQTT) broker gathers data from an IoT node and sends it to the computing platform for analysis. As a platform for the creation of several new technologies and applications, IoT has created new opportunities in the age of cloud communication. Due to the increasing use of cloud data warehouse technologies, computer networks have had serious security concerns, and there are security vulnerabilities in the IoT as well. DoS and DDoS attacks on IoT e-healthcare servers may compromise general stability, efficacy of the services, and real-time information federation. This study provided an efficient MQTT broker approach to secure servers from cyberattacks and presented state-of-the-art defenses against DoS/DDoS attacks in the IoT digital healthcare ecosystem.

• Publication Date: Mar 7, 2025
• Deposit Date: May 9, 2025
• Pages: 125-154
• Book Title: AI-Driven Healthcare Cybersecurity and Privacy
• Chapter Number: 5
• ISBN: 9798337328270 ; 9798337328287
• DOI: https://doi.org/10.4018/979-8-3373-2827-0.ch005