Modeling Credit Card Transaction Sequences to Detect and Prevent Fraudulent Activities

  • Unique Paper ID: 167000
  • Volume: 11
  • Issue: 3
  • PageNo: 108-112
  • Abstract:
  • Now a day the usage of credit cards has dramatically increased. As credit card becomes the most popular mode of payment for both online as well as regular purchase, cases of fraud associated with it are also rising. In this paper, we model the sequence of operations in credit card transaction processing can be used for the detection of frauds. An FDS is initially trained with the normal behavior of a cardholder. If an incoming credit card transaction is not accepted by the trained FDS with sufficiently high probability, it is considered to be fraudulent. At the same time, we try to ensure that genuine transactions are not rejected. We present detailed experimental results to show the effectiveness of our approach and compare it with other techniques available in the literature. This project is developing used to detect and block from fraud transactions using a credit card. Credit-card-based purchases can be categorized into two types: 1) physical card and 2) virtual card. In a physical-card based purchase, the cardholder presents his card physically to a merchant for making a payment. To carry out fraudulent transactions in this kind of purchase, an attacker has to steal the credit card. If the cardholder does not realize the loss of card, it can lead to a substantial financial loss to the credit card company. In the second kind of purchase, only some important information about a card (card number, expiration date, secure code) is required to make the payment. Such purchases are normally done on the Internet or over the telephone.

Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 3
  • PageNo: 108-112

Modeling Credit Card Transaction Sequences to Detect and Prevent Fraudulent Activities

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