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Dual Autoencoders Generative Adversarial Network for Fraud Detection of Credit Card
2020
IEEE Access
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INDEX TERMS Fraud detection, imbalanced classification, generative adversarial networks, autoencoders. ...
The imbalanced classification problem has become greatest issue in many fields, especially in fraud detection. ...
CONCLUSION In this work, we proposed a new neural network model DAEGAN to cope with imbalanced classification problem in credit card fraud detection. ...
doi:10.1109/access.2020.2994327
fatcat:okewn2wb7zhzzfynmr3nm2zdkq
Ensembled-based credit card fraud detection in online transactions
2022
AIP Conference Proceedings
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In this article, random forest and generative adversary networks are developed to further increase the accuracy of the detection rate of fraud via credit cards. ...
Fraud detection systems (FDS) are an important factor in e-commerce trading as online fraud grows and spreads quickly. ...
By ensembling the random forest with generative opposing networks, this paper will improve the accuracy of the credit card fraud detection rate. ...
doi:10.1063/5.0108873
fatcat:2jzvwaqc7jhixar7thtw3sby24
A Novel Approach to Credit Card Security with Generative Adversarial Networks and Security Assessment
2024
Journal of Social Science and Humanities
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This paper realizes credit card fraud detection by generating adversarial network technology, so as to prevent network security risks. ...
However, it is difficult for traditional means to effectively defend against undocumented fraud. ...
, particularly Generative Adversarial Networks (GANs), for credit card fraud detection. ...
doi:10.53469/wjimt.2024.07(02).03
fatcat:zhtrou6jdff4dpditvuawqukw4
Survey of Various Techniques used for Credit Card Fraud Detection
2020
International Journal for Research in Applied Science and Engineering Technology
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Government is making attempt to make India a digital country, So using an ATM or credit card is a convenient way of fulfilling the government's aim. ...
In today's era , technology is changing rapidly and with the increase in new innovations and advancements our way of life has changed . ...
Classification Techniques Different classification techniques have been applied for detecting the frauds that occur in credit card transactions.
1) Artificial neural network (ANN): It is known as a classifier ...
doi:10.22214/ijraset.2020.30614
fatcat:epycrw76sjhnnatrrkxvn7th4m
Credit card fraud detection and classification by deep learning and machine learning
2022
Global Journal of Engineering and Technology Advances
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These frauds are all examples of advanced fraud. This study makes three contributions toward the prevention of fraudulent activity involving credit card transactions. ...
In particular, over the recent past, there has been a significant increase in the utilization of credit and debit cards, whereby all customers trade transactions either digitally over the internet or physically ...
The credit card fraud detection methods using the deep learning methods are as follows, Zhou, X.-H.et al. [128] modelled a credit card fraud detection using a Generative adversarial network. ...
doi:10.30574/gjeta.2022.13.3.0202
fatcat:swqlh57xpvbdzh5kaizrnukjdu
GAN based Data Augmentation to Resolve Class Imbalance
[article]
2022
arXiv
pre-print
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We trained Generative Adversarial Network(GAN) to generate a large number of convincing (and reliable) synthetic examples of the minority class that can be used to alleviate the class imbalance within ...
The number of credit card fraud has been growing as technology grows and people can take advantage of it. ...
We chose a relevant paper "Using generative adversarial networks for improving classification effectiveness in credit card fraud detection" [8] , as our primary inspiration for training Generative Adversarial ...
arXiv:2206.05840v1
fatcat:cskkopipb5fjhf26yr5nkkp2ju
Using Variational Auto Encoding in Credit Card Fraud Detection
2020
IEEE Access
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INDEX TERMS Credit card fraud, variational automatic coding, oversampling, generative adversarial network, deep learning. ...
Machine learning approaches are widely used to analyze and detect the increasingly serious problem of credit card fraud. ...
which is a very effective solution for credit card fraud detection. ...
doi:10.1109/access.2020.3015600
fatcat:4glje5eanngqjeuxcurn7ua46e
Black-Box Adversarial Entry in Finance through Credit Card Fraud Detection
2021
International Conference on Information and Knowledge Management
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Despite processing sensitive information such as credit fraud detection and default payment prediction, a low depiction of the robustness of the financial machine learning algorithms can be dangerous. ...
One such application where little work has been done towards adversarial examples generation is financial systems. ...
SVM classifier have significant success in the binary classification tasks such as presentation attack detection [45, 46] and adversarial examples detection [34, 33] . ...
dblp:conf/cikm/0001R21
fatcat:cv647wb5ijgjldx4tx4phvfj4a
Adaptive Stress Testing for Adversarial Learning in a Financial Environment
[article]
2021
arXiv
pre-print
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We develop a simplified model for credit card fraud detection that utilizes a linear regression classifier based on historical payment transaction data coupled with business rules. ...
We demonstrate the use of Adaptive Stress Testing to detect and address potential vulnerabilities in a financial environment. ...
Related Work Most work in the area of adversarial learning in payment card fraud credits Liu and Chawla [6] as one of the earliest inspirations for this approach. ...
arXiv:2107.03577v1
fatcat:cifeuyjzsvbchc547mg7ozdj6a
Spectral-Cluster Solution For Credit-Card Fraud Detection Using A Genetic Algorithm Trained Modular Deep Learning Neural Network
2021
JINAV: Journal of Information and Visualization
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Study proposes a spectral-clustering hybrid of genetic algorithm trained modular neural network to detect fraud in credit card transactions. ...
The hybrid ensemble seeks to equip credit-card users with a system and algorithm whose knowledge will altruistically detect fraud on credit cards. ...
To overcome these pitfalls, we implement a genetic algorithm trained modular neural network deep learning approach to detect fraud on credit card network using the KDD dataset. ...
doi:10.35877/454ri.jinav274
fatcat:xrfdchg22fhylk76cd4ymlayri
Developing a Credit Card Fraud Detection Model using Machine Learning Approaches
2022
International Journal of Advanced Computer Science and Applications
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This research study aims to develop a credit-card fraud detection model that can effectively classify an online transaction as fraudulent or genuine. ...
Though there are several methods for completing online transactions, however, credit cards are most commonly used. ...
ACKNOWLEDGMENT The authors would like to thank the Deanship of Scientific Research at Majmaah University for supporting this work under project no: R-2022-50. ...
doi:10.14569/ijacsa.2022.0130350
fatcat:4w26ik3txrgf3iwgciizslaanu
Survey on Fraud Detection Techniques Using Data Mining
2015
International Journal of u- and e- Service, Science and Technology
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Internet Fraud is also very popular, where fraudster can steal the credit card number and buy thing from the different websites. ...
Fraud involves individual or in a form of groups who intentionally act secretly to rob another of something of worth, for their own profit. ...
Now a days, payment flows take place on line, So we need effective and well-organized systems for the finding of credit card fraud [16] . ...
doi:10.14257/ijunesst.2015.8.3.15
fatcat:abchv64nlzge3eq5vopzdtg4vm
A machine learning-based framework using the particle swarm optimization algorithm for credit card fraud detection
2023
Communications Faculty Of Science University of Ankara
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In this paper, we suggested a machine learning based methodology to detect fraud in credit cards. ...
The detection of fraudulent activities in credit cards transactions presents a significant challenge due to the constantly changing and unpredictable tactics used by fraudsters, who take advantage of technological ...
Proposed Model for Credit Card Fraud Detection This section presents the suggested framework for fraud detection. ...
doi:10.33769/aupse.1361266
fatcat:oratsdtak5gd3d2d7tesr2ghvi
An Efficient Domain-Adaptation Method using GAN for Fraud Detection
2020
International Journal of Advanced Computer Science and Applications
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In this paper, an efficient domain-adaptation method is proposed for fraud detection. ...
The proposed method employs the discriminative characteristics used in feature maps and generative adversarial networks (GANs), to minimize the deviation that occurs when a common feature is shifted between ...
In the experiments, credit card and financial transaction fraud datasets were used to evaluate the model's performance. ...
doi:10.14569/ijacsa.2020.0111113
fatcat:7bdimlw6wbholnvzvwpxg2xapu
Limitations and Applicability of GANs in Banking Domain
2020
European Conference on Artificial Intelligence
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In this paper, we present a systematic study to train GANs for synthetic fraud generation, demonstrating improved classifier performance detecting fraud. ...
The performance comparison of different settings proposed in this study is evaluated using a publicly available Credit-Card dataset and showed an absolute improvement of up to 6% in Recall and 3% in precision ...
in credit card fraud detection. ...
dblp:conf/ecai/PandeyBB20
fatcat:uyzp4kn7zbamvpg7o5m76nsc5q
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