An AI-Driven Cloud Framework for Cybersecurity and Financial Fraud Detection with Medical Image Analysis and 5G-Enabled Web Applications
Abstract
The convergence of artificial intelligence (AI), cloud computing, and 5G connectivity is reshaping modern digital ecosystems by enabling advanced real-time applications across multiple domains. This study proposes an AI-driven cloud framework that integrates cybersecurity, financial fraud detection, and medical image analysis within a unified 5G-enabled web application environment. The framework leverages cloud-native services for scalable data storage, processing, and deployment, while utilizing AI algorithms for anomaly detection, pattern recognition, and predictive analytics. In cybersecurity, the system employs machine learning models to detect intrusions, malware, and network anomalies in real time. For financial fraud detection, supervised and unsupervised learning models analyze transactional data to identify suspicious patterns and prevent fraudulent activities. Medical image analysis utilizes deep learning techniques for disease detection and diagnosis, supporting healthcare professionals with accurate and timely insights. The 5G-enabled web application layer ensures ultra-low latency and high throughput, enabling seamless access to AI services on mobile and IoT devices. The proposed framework enhances security, reliability, and efficiency across multiple sectors while providing a scalable, interoperable platform for future AI-driven applications.
Article Information
Journal |
International Journal of Future Innovative Science and Technology (IJFIST) |
|---|---|
Volume (Issue) |
Vol. 5 No. 5 (2022): International Journal of Future Innovative Science and Technology (IJFIST) |
DOI |
|
Pages |
9189-9196 |
Published |
September 5, 2022 |
| Copyright |
All rights reserved |
Open Access |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
How to Cite |
Liam Alexander Smith (2022). An AI-Driven Cloud Framework for Cybersecurity and Financial Fraud Detection with Medical Image Analysis and 5G-Enabled Web Applications. International Journal of Future Innovative Science and Technology (IJFIST) , Vol. 5 No. 5 (2022): International Journal of Future Innovative Science and Technology (IJFIST) , pp. 9189-9196. https://doi.org/10.15662/IJFIST.2022.0505002 |
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