A Secure Federated Cyber Security Model Using Distributed Artificial Intelligence For Healthcare Cloud And Iot Applications

Abstract

The fast penetration of cloud computing, Internet of Things (IoT) systems, and distributed healthcare systems have greatly changed the contemporary healthcare systems by introducing the ability to monitor the patients remotely, smart diagnostics, real-time healthcare data analytics, and connected medical care. Nonetheless, the growing adoption of IoT-enabled medical devices, wearable health devices, cloud-based health platforms, and distributed networks of healthcare communications, has come at the cost of critical cybersecurity risks linked to data breaches, ransomware attacks, unauthorized access, adversarial intrusion and distributed denial-of-service attacks. Traditional centralized cybersecurity architectures are often limited in terms of scalability, slow intrusion detection response, the threat of privacy leakages, and ineffective scalability to dynamically changing cyber threat conditions. The current paper suggests a federated model of cyberspace security by incorporating federated intrusion intelligence, federated anomaly detection, using edge-assisted threat monitoring, adaptive trust management, and privacy-preserving cybersecurity coordination mechanisms, Secure Federated Cyber Security Model Using Distributed Artificial Intelligence to healthcare cloud and IoT applications. The suggested architecture includes distributed intrusion prediction with the help of artificial intelligence and based on encrypted federated learning, behavioral monitoring of the IoT, adaptive assessment of cyber risks, and explainable threat intelligence to enhance healthcare cybersecurity resilience and distributed threat mitigation capacity. The model also includes secure healthcare communication synchronization, federated attack detection, adversarial behavior analysis, and distributed trust verification to scale to cyber defense in healthcare environments in the cloud and IoT. Experimental analysis reveals that accuracy of cyberattack detection, distributed intrusion mitigation, healthcare communication security, resilience to adversarial attacks, and scalability of federated cybersecurity is much higher than the traditional healthcare cybersecurity systems. The suggested framework thus offers a scalable and safe distributed architecture of cybersecurity to support the next-generation cloud and IoT application to healthcare.