Intelligent API Governance using Advanced Machine Learning for Secure Cloud Native Enterprise Application Modernization
Abstract
Enterprise application modernization is increasingly driven by cloud-native architectures, microservices, containers, serverless computing, and application programming interfaces (APIs). While these technologies improve scalability, agility, and interoperability, they also create complex API ecosystems that are difficult to govern, secure, monitor, and maintain. Conventional API governance approaches depend heavily on manually defined policies, static rules, documentation, and periodic audits, limiting their ability to respond effectively to rapidly changing cloud-native environments. This research proposes an intelligent API governance framework using advanced machine learning to support secure cloud-native enterprise application modernization. The proposed framework combines API discovery, machine-learning-based risk classification, behavioral analytics, security policy enforcement, anomaly detection, lifecycle management, compliance assessment, and intelligent decision support. Machine learning models analyze API specifications, traffic patterns, configuration information, authentication behavior, dependencies, and operational telemetry to identify security vulnerabilities, policy violations, anomalous behavior, deprecated interfaces, and modernization risks. The framework also incorporates explainable recommendations and human approval for high-impact governance decisions. A design science and experimental research methodology is proposed to develop and evaluate the framework using representative enterprise API environments. Evaluation focuses on governance accuracy, security detection, policy-compliance rate, false positives, anomaly detection, modernization efficiency, processing latency, and reduction in manual governance effort. The research aims to demonstrate how machine learning can transform API governance into a proactive, adaptive, and security-aware capability that supports reliable and controlled enterprise modernization
Article Information
Journal |
International Journal of Science, Research and Technology |
|---|---|
Volume (Issue) |
Vol. 6 No. 6 (2023): International Journal of Science, Research and Technology (IJSRAT) |
DOI |
|
Pages |
11120-11131 |
Published |
December 16, 2023 |
| Copyright |
All rights reserved |
Open Access |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
How to Cite |
Subramanian Ramamoorthy (%2023). Intelligent API Governance using Advanced Machine Learning for Secure Cloud Native Enterprise Application Modernization. International Journal of Science, Research and Technology , Vol. 6 No. 6 (2023): International Journal of Science, Research and Technology (IJSRAT) , pp. 11120-11131. https://doi.org/10.15662/IJSRAT.2023.0606012 |
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