Approaches to Hybrid Data Mining for the Determination of Financial Transaction System Fraud Fasi Ahmed Parvez Mohammad1, Dr. Manisha2

Authors

  • Fasi Ahmed Parvez Mohammad, Dr. Manisha Author

Keywords:

Serverless Computing, AWS Lambda, Azure Functions, Microservices Security, Cloud-Native Architecture, Access Control

Abstract

Cloud-native application development adopting Serverless computing is transforming application development through the speed of deployment, scalability and without the requirement to manage the infrastructure. The literature explores security architectures of AWS Lambda and Azure Functions on important aspects like authentication, data encryption and microservices access control. This is a study using an explanatory research design and secondary qualitative and quantitative data to compare the strengths and weaknesses of the security features of each platform. The results show the need to have least privilege access; use of controls, like firewalls and intrusion prevention systems; and real time monitoring to balance the vulnerabilities. This is essential for performance, compliance and resilience in such a dynamic environment where security strategies and tools are their top priority.

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Published

2025-04-04

How to Cite

Approaches to Hybrid Data Mining for the Determination of Financial Transaction System Fraud Fasi Ahmed Parvez Mohammad1, Dr. Manisha2. (2025). International IT Journal of Research, ISSN: 3007-6706, 3(2), 31-37. https://itjournal.org/index.php/itjournal/article/view/138

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