Reliable and Secure SDN/NFV-Based 5G Cloud Networks for AI-Powered Healthcare, Fraud Detection, and Industrial Analytics

Noor Elisabeth Visser

doi:10.15662/IJRAI.2021.0406013

Authors

Noor Elisabeth Visser Senior Data Engineer, Netherlands Author

DOI:

https://doi.org/10.15662/IJRAI.2021.0406013

Keywords:

5G Networks, SDN, NFV, Cloud Computing, Artificial Intelligence, Healthcare Analytics, Fraud Detection, Industrial Analytics, Network Security, Reliability

Abstract

The rapid deployment of 5G networks and cloud-based infrastructures has accelerated the adoption of artificial intelligence (AI) in healthcare, financial fraud detection, and industrial analytics. However, traditional network architectures face challenges in meeting stringent requirements for reliability, security, scalability, and low latency demanded by these mission-critical applications. Software-Defined Networking (SDN) and Network Function Virtualization (NFV) offer programmable and flexible network management capabilities that can address these challenges when integrated with cloud and AI technologies. This paper presents a reliable and secure SDN/NFV-based 5G cloud network framework designed to support AI-powered healthcare services, real-time fraud detection, and intelligent industrial analytics. The proposed architecture enables dynamic traffic management, adaptive security enforcement, and efficient resource utilization while ensuring data privacy and service continuity. AI-driven analytics enhance predictive decision-making, anomaly detection, and operational intelligence across heterogeneous environments. The framework is evaluated conceptually across healthcare, financial, and industrial use cases, demonstrating its ability to improve reliability, reduce latency, mitigate cyber threats, and support large-scale deployments. The study highlights the importance of integrated network intelligence and security for next-generation digital ecosystems.

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