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Credit Card Fraud Detection using Big Data Analytics: Use of PSOAANN based One-Class Classification

Authors:

Sk. Kamaruddin,

Vadlamani RaviAuthors Info & Claims

ICIA-16: Proceedings of the International Conference on Informatics and Analytics

Article No.: 33, Pages 1 - 8

https://doi.org/10.1145/2980258.2980319

Published: 25 August 2016 Publication History

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Abstract

Banking and financial industries are facing severe challenges in the form of fraudulent transactions. Credit card fraud is one example of them. In order to detect credit card fraud, we employed one-class classification approach in big data paradigm. We implemented a hybrid architecture of Particle Swarm Optimization and Auto-Associative Neural Network for one-class classification in Spark computational framework. In this paper, we implemented parallelization of the auto-associative neural network in the hybrid architecture.

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Jahnavi DA MPulata SSami SVakamullu BMohan G B(2024)Robust Hybrid Machine Learning Model for Financial Fraud Detection in Credit Card Transactions2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT)10.1109/IDCIoT59759.2024.10467340(680-686)Online publication date: 4-Jan-2024
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ICIA-16: Proceedings of the International Conference on Informatics and Analytics

August 2016

868 pages

ISBN:9781450347563

DOI:10.1145/2980258

Copyright © 2016 ACM.

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Published: 25 August 2016

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ICIA-16: International Conference on Informatics and Analytics

August 25 - 26, 2016

Pondicherry, India

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Cited By

Pei WXue BZhang MShang LYao XZhang Q(2024)A Survey on Unbalanced Classification: How Can Evolutionary Computation Help?IEEE Transactions on Evolutionary Computation10.1109/TEVC.2023.325723028:2(353-373)Online publication date: Apr-2024
https://doi.org/10.1109/TEVC.2023.3257230
Jahnavi DA MPulata SSami SVakamullu BMohan G B(2024)Robust Hybrid Machine Learning Model for Financial Fraud Detection in Credit Card Transactions2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT)10.1109/IDCIoT59759.2024.10467340(680-686)Online publication date: 4-Jan-2024
https://doi.org/10.1109/IDCIoT59759.2024.10467340
Jhansi Ida SBalasubadra KR R ST L(2024)Enhancing Credit Card Fraud Detection through LSTM-Based Sequential Analysis with Early Stopping2024 2nd International Conference on Networking and Communications (ICNWC)10.1109/ICNWC60771.2024.10537550(1-6)Online publication date: 2-Apr-2024
https://doi.org/10.1109/ICNWC60771.2024.10537550
Jain SAsha S(2024)Credit Card Fraud Detection System using SMOTEENN and Adaptive XGBoost and comparing the result with state-of-art-technique2024 IEEE 9th International Conference for Convergence in Technology (I2CT)10.1109/I2CT61223.2024.10543887(1-7)Online publication date: 5-Apr-2024
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Abdul Salam MFouad KElbably DElsayed S(2024)Federated learning model for credit card fraud detection with data balancing techniquesNeural Computing and Applications10.1007/s00521-023-09410-236:11(6231-6256)Online publication date: 20-Jan-2024
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Kakkar SB SReddy LPal SDimri SNishant N(2023)Analysis of Discovering Fraud in Master Card Based on Bidirectional GRU and CNN Based Model2023 International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS)10.1109/ICSSAS57918.2023.10331770(50-55)Online publication date: 18-Oct-2023
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