Please use this identifier to cite or link to this item: http://202.88.229.59:8080/xmlui/handle/123456789/5724
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dc.contributor.authorDr.Meenu Suresh-
dc.date.accessioned2025-01-21T09:28:03Z-
dc.date.available2025-01-21T09:28:03Z-
dc.date.issued2024-04-
dc.identifier.urihttp://202.88.229.59:8080/xmlui/handle/123456789/5724-
dc.description.abstractElectronic 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.isoenen_US
dc.publisherJournal of Nonlinear Analysis and Optimization: Theory & Applicatiansen_US
dc.titleCREDIT CARD FRAUD ANALYSIS AND DETECTION METHODen_US
dc.typeArticleen_US
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