CNN-Bidirectional LSTM based Approach for Financial Fraud Detection and Prevention System

Author:

Reddy N. Madhusudhana1,Sharada K A2,Pilli Daniel3,Paranthaman R.Nithya4,Reddy K Subba5,Chauhan Amit6

Affiliation:

1. Rajeev Gandhi Memorial College of Engineering and Technology,Department of CSE,Nandyal,Andhra Pradesh,India

2. HKBK College of Engineering,Department of CSE,Bangalore,Karnataka,India

3. Koneru Lakshmaiah Educational Foundation,MBA Department,Andhra Pradesh,India

4. School of Computing, College of Engineering and Technology, SRM Institute of Science and Technology,Department of Networking and Communications,Tamilnadu,India

5. Prakasam Engineering College,Department of Computer Science and Engineering,Kandukur,Andhra Pradesh,India

6. CHRIST (Deemed to be University),Department of Life Sciences,Bengaluru,Karnataka,India

Publisher

IEEE

Reference27 articles.

1. ISMA: Intelligent Sensing Model for Anomalies Detection in Cross Platform OSNs With a Case Study on IoT

2. Testing the Fraud Detection Ability of Different User Profiles by Means of FF-NN Classifiers

3. Systems and methods for online fraud detection;favila,2019

4. A Comprehensive Survey of Data Mining-based Fraud Detection Research;phua,2010

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2. Machine Learning-Powered Fraud Detection & Prevention: A Comprehensive Implementation;2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT);2024-01-04

3. Analysis of Discovering Fraud in Master Card Based on Bidirectional GRU and CNN Based Model;2023 International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS);2023-10-18

4. Comparative Evaluation of Fraud Detection in Online Payments Using CNN-BiGRU-A Approach;2023 International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS);2023-10-18

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