Low Cost Journal,International Peer Reviewed and Refereed Journals,Fast Paper Publication approved journal IJEDR(ISSN 2321-9939) apply for ugc care approved journal, UGC Approved Journal, ugc approved journal, ugc approved list of journal, ugc care journal, care journal, UGC-CARE list, New UGC-CARE Reference List, UGC CARE Journals, ugc care list of journal, ugc care list 2020, ugc care approved journal, ugc care list 2020, new ugc approved journal in 2020, Low cost research journal, Online international research journal, Peer-reviewed, and Refereed Journals, scholarly journals, impact factor 7.37 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool)
INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH
(International Peer Reviewed,Refereed, Indexed, Citation Open Access Journal)
ISSN: 2321-9939 | ESTD Year: 2013

Current Issue

Call For Papers
June 2023

Volume 11 | Issue 2
Last Date : 29 June 2023
Review Results: Within 12-20 Days

For Authors

Archives

Indexing Partner

Research Area

LICENSE

Paper Details
Paper Title
survey on credit card fraud detection using data mining techniques
Authors
  Anusha S,  Deepika N

Abstract
Credit card fraud detection is a wide-ranging term for theft and fraud committed using or involving a payment card, such as a credit card or debit card, as a fraudulent source of funds in a transaction. Due to fast growth of E-Commerce, use of credit card for online purchases has dramatically increased and it caused and increase in the credit card fraud. As credit card has become the most popular mode of payment for online and regular purchase, frauds associated with it are rising. In real life, fraudulent transactions are scattered with real transactions and simple pattern matching techniques are not often sufficient to detect those frauds accurately. Many techniques based on data mining, Random Forest, Machine Learning has involved in detecting various credit card fraudulent transactions. Credit card fraud detection is a wide-ranging term for theft and fraud committed using or involving a payment card, such as a credit card or debit card, as a fraudulent source of funds in a transaction. Due to fast growth of E-Commerce, use of credit card for online purchases has dramatically increased and it caused and increase in the credit card fraud. As credit card has become the most popular mode of payment for online and regular purchase, frauds associated with it are rising. In real life, fraudulent transactions are scattered with real transactions and simple pattern matching techniques are not often sufficient to detect those frauds accurately. Many techniques based on data mining, Random Forest, Machine Learning has involved in detecting various credit card fraudulent transactions.

Keywords- Fraud Detection, Machine Learning, Random Forest, Spark, Semi-Supervised Learning Techniques
Publication Details
Unique Identification Number - IJEDR1804104
Page Number(s) - 590-592
Pubished in - Volume 6 | Issue 4 | December 2018
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Anusha S,  Deepika N,   "survey on credit card fraud detection using data mining techniques", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.6, Issue 4, pp.590-592, December 2018, Available at :http://www.ijedr.org/papers/IJEDR1804104.pdf
Share This Article


Article Preview

ISSN Details




DOI Details



Providing A digital object identifier by DOI
How to get DOI?

For Reviewer /Referral (RMS)

Important Links

NEWS & Conference

Digital Library

Our Social Link

© Copyright 2024 IJEDR.ORG All rights reserved