Intelligent Access Control for Secure Financial Microservices Using AI-Driven Threat Detection and Risk Analytics

Authors

  • Dr. A. Rengarajan Professor, School of Computer Science and Information Technology, Jain University, Bengaluru, India. Author

DOI:

https://doi.org/10.63282/3050-9246.IJETCSIT-V5I1P124

Keywords:

Financial Microservices, Intelligent Access Control, Zero-Trust Security, Artificial Intelligence, Threat Detection, Risk Analytics, Explainable AI

Abstract

Tackling distributed authentication, inter-service communication, untrusted APIs as well as the ever-evolving cyber threat and fraudulent transaction landscape are all major issues in today's financial application microservice era. The standard methodologies of controlling access – especially static RBAC – are not as contextually aware or flexible as necessary to safeguard the changing relationships among money. This study suggests an intelligent setup of an access control system that integrates Zero Trust Security (ZTS), Artificial Intelligence (AI) based threat detection, Dynamic Trust Assessment (DTA) and Financial Risk Analytics (FRA) to enhance the security of Financial microservices. All the above is covered in one security architecture and framework; ID verification, contextual authorization, API anomaly detection and behavior analysis and explainable risk assessment. Machine learning models are used to analyze the trends of API calls, service interactions across distributed systems, authentication events and behavior indicators of transactions to detect potentially malicious activity. A dynamic policy engine is then used to determine which ones are granted access for, depending on the risk assessment and vulnerabilities of the service and security context. Explainable AI mechanisms offer insight to authorisation decisions while privacy aware information sharing enables safe collaboration, of financial services dispersed at locations. A critical analysis of the proposed framework of architecture in terms of feasibility, scalability, robustness, interpretability and applicability to the operation is provided. To enhance the resilience and trustworthiness of financial microservice ecosystem, the concept of integrated security solution: intelligent threat detection & adaptive authorization and financial risk management is proposed in the article.

References

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Published

2024-02-29

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Articles

How to Cite

A, R. (2024). Intelligent Access Control for Secure Financial Microservices Using AI-Driven Threat Detection and Risk Analytics. International Journal of Emerging Trends in Computer Science and Information Technology, 5(1), 241-250. https://doi.org/10.63282/3050-9246.IJETCSIT-V5I1P124

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