AI-Powered Threat Intelligence for Proactive Risk Detection in 5G-Enabled Smart Healthcare Communication Networks

Abstract

The convergence of Artificial Intelligence (AI) and 5G technology in smart healthcare communication networks offers transformative capabilities, enabling real-time diagnostics, remote surgeries, continuous patient monitoring, and high-speed medical data exchange. However, this integration also introduces new and complex cybersecurity threats, ranging from data breaches and denial-of-service attacks to AI model manipulation and privacy violations. This review explores the potential of AI-powered threat intelligence systems in proactively identifying, predicting, and mitigating cybersecurity risks in 5G-enabled smart healthcare ecosystems. Emphasis is placed on how AI techniques such as machine learning, deep learning, and natural language processing can automate threat detection, anomaly identification, and threat actor profiling in dynamic and latency-sensitive healthcare environments. Furthermore, the study analyzes how federated learning, edge AI, and explainable AI enhance data security, maintain patient confidentiality, and ensure compliance with regulatory frameworks such as HIPAA and GDPR. By surveying recent advances in threat intelligence platforms and examining their integration with 5G infrastructure, this paper highlights the critical role of AI in establishing resilient, adaptive, and secure healthcare communication systems. The review concludes with a discussion of open challenges, ethical considerations, and future research directions for AI-driven security architectures in next-generation medical networks.

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