AN AI-AUGMENTED FRAMEWORK FOR FRAUD DETECTION AND ANOMALY SUPPRESSION IN EVENT-DRIVEN MULESOFT PAYMENT GATEWAYS USING DEVOPS PIPELINES
DOI:
https://doi.org/10.48047/8jawqc81Keywords:
Artificial Intelligence, Fraud Detection, MuleSoft, DevOps, Payment Gateways, Anomaly Detection, CI/CD Pipelines, Machine Learning, Financial Security.Abstract
Using AI, fraud detection and anomaly suppression safeguarding MuleSoft payment gateways, it can automate the detection and prevention of fraud forces, making things easier and safer. This new system uses machine learning together with DevOps CI/CD pipelines to identify fraud right away and respond to threats automatically. This project introduces a broad method to deal
serious issues in payment systems
Downloads
Downloads
Published
Issue
Section
License
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
