2020 4th International Conference on Intelligent Computing and Control Systems (ICICCS) 2020
DOI: 10.1109/iciccs48265.2020.9120957
|View full text |Cite
|
Sign up to set email alerts
|

Credit Card Fraud Detection using Artificial Neural Network and BackPropagation

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
4
0
2

Year Published

2021
2021
2023
2023

Publication Types

Select...
4
4

Relationship

0
8

Authors

Journals

citations
Cited by 28 publications
(13 citation statements)
references
References 11 publications
0
4
0
2
Order By: Relevance
“…The results showed that the ANN was the best among the other models, with an Accuracy of 99.92%, a Precision of 81.15%, and a Recall of 76.19%. Dubey et al [1] conducted an experiment on the Credit Card Customer dataset with the use of ANN. That processed the data in the first layer, which was the input layer, and then the hidden layer, which had 15 neurons and the use of the RELU activation function, and then the output layer, which used the Sigmoid activation function.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…The results showed that the ANN was the best among the other models, with an Accuracy of 99.92%, a Precision of 81.15%, and a Recall of 76.19%. Dubey et al [1] conducted an experiment on the Credit Card Customer dataset with the use of ANN. That processed the data in the first layer, which was the input layer, and then the hidden layer, which had 15 neurons and the use of the RELU activation function, and then the output layer, which used the Sigmoid activation function.…”
Section: Related Workmentioning
confidence: 99%
“…The impact of online financial losses cannot be underestimated. Once fraudsters steal card details, they can use the cards themselves or sell the card details to other people, as is the case in India, where the card details of around 70 million people are being sold on the dark web [1]. One of the most serious credit card fraud incidents in recent memory that took place in the UK resulted in GBP 17 million total in financial losses.…”
Section: Introductionmentioning
confidence: 99%
“…This study uses the dataset of September 2013 credit card transactions provided on Kaggle [13]. This dataset is widely used to test the proposed learning model by many studies [9], [16] to detect fraudulent transactions. It comprised 284,807 transactions, of which 492 were fraudulent.…”
Section: Dataset Descriptionmentioning
confidence: 99%
“…10 We also divide our datasets into traditional 80% (training size) and 20% (test size) for our experimental analysis. 34…”
Section: Experimental Evaluationmentioning
confidence: 99%