Credit Card Fraud Detection Using State-of-the-Art Machine Learning and Deep Learning Algorithms

Authors

  • Dr. Narendra Kumar, I Divya SrI, Basu Lakshmi Prasanna, Pemmaraju Sumaja

Keywords:

CNN , Backing Vector Machine Hybrid Encryption, Mobile Ad hoc Network, Security XGBoost.

Abstract

Visas are generally utilized for online exchanges because of their proficiency and usability. Nonetheless,with the ascent in Mastercard use, the potential for abuse has additionally expanded. Visa misrepresentation brings about huge monetary misfortunes for the two cardholders and monetary organizations. Our essential objective is to recognize such fakes, taking into account the difficulties of
public information availability, elegant awkwardness in information, advancing nature of extortion, and high misleading problem rates.

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References

Y. Abakarim, M. Lahby, and A. Attioui, ``An ef_cient real time model for credit card fraud detection based on deep learning,'' in Proc.

th Int. Conf. Intell. Systems: Theories Appl., Oct. 2018, pp. 1_7, doi: 10.1145/3289402.3289530.

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Published

2023-12-24

How to Cite

Dr. Narendra Kumar, I Divya SrI, Basu Lakshmi Prasanna, Pemmaraju Sumaja. (2023). Credit Card Fraud Detection Using State-of-the-Art Machine Learning and Deep Learning Algorithms. Pegem Journal of Education and Instruction, 13(4), 607–614. Retrieved from https://pegegog.net/index.php/pegegog/article/view/4026

Issue

Vol. 13 No. 4 (2023): PEGEGOG

Section

Article

License

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