Building a CNN model for Credit card fraud detection using TensorFlow and Keras

Building a CNN model for Credit card fraud detection using TensorFlow and Keras

Registration ID: IJNRD_217367

Published ID: IJNRD2404155

DOI: Click Here to Get

G. Vijaya Lakshmi , Sumeet Sai Mahapatro , V. Monica , S. Sowjanya

Convolutional Neural Networks (CNN), Credit Card Fraud Detection, TensorFlow, Keras, Model Training and Validation, Machine Learning, Dataset Splitting, Precision, Recall, F1 Score, Feature Extraction.

This study presents a novel approach to fraud detection using convolutional neural networks (CNNs) in the digital finance sector. The model is trained on a complex dataset of legitimate and fraudulent credit card transactions, highlighting patterns and transaction characteristics indicative of fraudulent activity. The model is designed to capture complex patterns and adapt to evolving fraud tactics. The performance of the model is evaluated against traditional methods, focusing on accuracy, precision, recall, and F1 score. The study also explores the implications of false positives and false negatives in credit card fraud detection. The research also addresses challenges in real-world scenarios, proposing a solution for integrating the CNN model into existing systems. The study also addresses ethical considerations and privacy concerns, proposing responsible use guidelines to balance the benefits of improved fraud detection with user data protection.

Published Paper   E-Certificate

"Building a CNN model for Credit card fraud detection using TensorFlow and Keras", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 4, page no.b425-b434, April-2024, Available :https://ijnrd.org/papers/IJNRD2404155.pdf

Volume 9 Issue 4, April-2024

Pages : b425-b434

Paper Reg. ID: IJNRD_217367

Published Paper Id: IJNRD2404155

Downloads: 000121155

Research Area: Computer Science & Technology 

Country: Srikakulam, Andhra Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404155.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404155

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 8 | August 2025

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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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