INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
Electronic trade or web based business is a plan of action that lets organizations and people over the web trade anything. As of late, in the age of the Internet and sending to E-business, parts of information are put away and moved starting with one area then onto the next. Information that moved can be presented to risk by fraudsters. There is an enormous expansion in misrepresentation which is prompting the deficiency of a huge number of dollars worldwide consistently. There are different current methods of distinguishing extortion that is consistently proposed and applied to a few business fields. The primary undertaking of Fraud identification is to notice the activities of huge loads of clients to recognize undesirable conduct. To recognize these different sorts, information mining strategies and AI to have been proposed and carried out to decrease down the assaults. A quite some time ago, numerous strategies are used for misrepresentation discovery framework like Support Vector Machine (SVM), K-closest Neighbor (KNN), neural organizations (NN), Fuzzy Logic, Decision Trees, and numerous more. This large number of methods have yielded respectable outcomes yet expecting to further develop the precision even further, by fostering the actual strategies or by utilizing a crossover learning approach for distinguishing cheats.
Keywords:
Monitoring, Credit Card, Authentication, security
Cite Article:
"Credit Card Fraud Detection-E-commerce", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 5, page no.389 - 392, May-2022, Available :http://www.ijsdr.org/papers/IJSDR2205074.pdf
Downloads:
000336256
Publication Details:
Published Paper ID: IJSDR2205074
Registration ID:200426
Published In: Volume 7 Issue 5, May-2022
DOI (Digital Object Identifier):
Page No: 389 - 392
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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