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effective tracking of fraudulent action from multi fund transaction using big data and machine learning

T.A.Vinayagam ,Sathish Kiran V ,Mutharasan.R,Venkatesh Reddy.V

Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology

ISSN: 2321-3337          Impact Factor:1.521         Volume:6         Issue:3         Year: 22 April,2024         Pages:1844-1851

International Journal of Advanced Research in Computer Science Engineering and Information Technology

Abstract

In scenarios involving cloud services, a key challenge arises from the potential differences in how cloud vendors isolate and connect virtual machines across various cloud networks. Our approach addresses this challenge by prioritizing the tenant's needs, allowing them to dictate their preferred connectivity methods. We integrate Blockchain technology into this project, enabling secure and transparent data management. Our implementation encompasses both Public and Private cloud data storage, with Private storage reserved for sensitive data while Public storage caters to regular data needs. Specifically tailored for the banking sector, our system aims to analyze user behavior while safeguarding personal information. It achieves this by aggregating and monitoring all user transactions, including banking activities, land registrations, gold purchases, and any cash transactions exceeding Rs. 20,000.

Kewords

Cloud services, virtual machines, cloud networks, tenant-driven approach, Block chain technology, banking system, user behavior, personal identification, transactions, integration, sensitive data, transparency.

Reference

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