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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 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.15 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Credit Card Fraud Detection Using Machine Learning |
| Authors Name: | Shital V. Avhad , Nilam B. Avhad , Pooja K. Palve , Komal D. Sanap , Dr. Swati A. Bhavsar |
| Unique Id: | IJSDR2305141 |
| Published In: | Volume 8 Issue 5, May-2023 |
| Abstract: | 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 Using Machine Learning ", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 5, page no.927 - 931, May-2023, Available :http://www.ijsdr.org/papers/IJSDR2305141.pdf |
| Downloads: | 000223171 |
| Publication Details: | Published Paper ID: IJSDR2305141 Registration ID:206403 Published In: Volume 8 Issue 5, May-2023 DOI (Digital Object Identifier): Page No: 927 - 931 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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