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CREDIT CARD FRAUD ANALYSIS AND DETECTION METHOD

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dc.contributor.author Dr.Meenu Suresh
dc.date.accessioned 2025-01-21T09:28:03Z
dc.date.available 2025-01-21T09:28:03Z
dc.date.issued 2024-04
dc.identifier.uri http://202.88.229.59:8080/xmlui/handle/123456789/5724
dc.description.abstract Electronic payment (e-payment) has transformed financial transactions, offering speed and convenience. However, it has also brought about significant challenges, notably in credit card security. This paper explores the landscape of e-payment, focusing on credit card fraud detection—a crucial aspect of financial security systems. Advanced algorithms and machine learning techniques are employed to analyse transaction data for patterns indicative of fraudulent activity. Despite these advancements, credit cards face various security threats, including card skimming, phishing scams, and data breaches. Cybercriminals continuously adapt their tactics, necessitating ongoing advancements in credit card protection. This paper highlights the importance of evolving security measures to safeguard users' financial information in the ever-changing digital landscape. en_US
dc.language.iso en en_US
dc.publisher Journal of Nonlinear Analysis and Optimization: Theory & Applicatians en_US
dc.title CREDIT CARD FRAUD ANALYSIS AND DETECTION METHOD en_US
dc.type Article en_US


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