Credit Card-Based Secure Online Payment

In this paper we use online payment gateways for payment systems even for ticket booking or movie ticketing. In that we use our credit card for payment. There is no security as we use credit card. More hacking is taking place. In this system, we are using hybrid technology and two layer security for the ticket booking process. With this we are bringing more secured transactions. In the first method SMS is used and in the second method browser based ticketing system is used. In the SMS model user will be giving their account number, pin number, withdrawal amount as text SMS to the GSM modem connected to the bank server. The bank server verifies account number and the pin number and the balance amount in the user account then generates OTP along with the bank’s ID to the user’s mobile number.Then user logins to the merchant (eg. cinema theatre) website gives the pin number along with the bank id using their own keypad matrix. This data is encrypted and sent to the merchant’s URL for the security purpose. At the initial point of registration bank provides a unique keypad ID for every user. The Merchant’s website will forward the pin number of the user to the corresponding bank. Bank will verify the OTP as well as keypad ID. If both are matched corresponding amount requested by the user is transferred to the merchant. Then the merchant issues the ticket to the user.In Modification phase, each key which is provided by the bank will have the expiration time that means if the key has two hours of time limit. Then we have to use the key within two hours else the amount will be reverted back to the corresponding account.

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Data Mining for Secure Online Payment Transaction

Digital Currency ◽

10.4018/978-1-5225-6201-6.ch016 ◽

2018 ◽

pp. 286-312

Author(s):

Masoumeh Zareapoor ◽

Pourya Shamsolmoali ◽

M. Afshar Alam

Keyword(s):

Data Mining ◽

Credit Card ◽

Detection Rate ◽

Detection System ◽

Fraud Detection ◽

Holistic Approach ◽

False Alarms ◽

Detection Systems ◽

Online Payment ◽

Proposed Model

The fraud detection method requires a holistic approach where the objective is to correctly classify the transactions as legitimate or fraudulent. The existing methods give importance to detect all fraudulent transactions since it results in money loss. For this most of the time, they have to compromise on some genuine transactions. Thus, the major issue that the credit card fraud detection systems face today is that a significant percentage of transactions labelled as fraudulent are in fact legitimate. These “false alarms” delay the transactions and creates inconvenience and dissatisfaction to the customer. Thus, the objective of this research is to develop an intelligent data mining based fraud detection system for secure online payment transaction system. The performance evaluation of the proposed model is done on real credit card dataset and it is found that the proposed model has high fraud detection rate and less false alarm rate than other state-of-the-art classifiers.

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Data Mining for Secure Online Payment Transaction

Advances in Business Information Systems and Analytics - Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence ◽

10.4018/978-1-5225-2031-3.ch005 ◽

2017 ◽

pp. 62-89

Author(s):

Masoumeh Zareapoor ◽

Pourya Shamsolmoali ◽

M. Afshar Alam

Keyword(s):

Data Mining ◽

Credit Card ◽

Detection Rate ◽

Detection System ◽

Fraud Detection ◽

Holistic Approach ◽

False Alarms ◽

Detection Systems ◽

Online Payment ◽

Proposed Model

The fraud detection method requires a holistic approach where the objective is to correctly classify the transactions as legitimate or fraudulent. The existing methods give importance to detect all fraudulent transactions since it results in money loss. For this most of the time, they have to compromise on some genuine transactions. Thus, the major issue that the credit card fraud detection systems face today is that a significant percentage of transactions labelled as fraudulent are in fact legitimate. These “false alarms” delay the transactions and creates inconvenience and dissatisfaction to the customer. Thus, the objective of this research is to develop an intelligent data mining based fraud detection system for secure online payment transaction system. The performance evaluation of the proposed model is done on real credit card dataset and it is found that the proposed model has high fraud detection rate and less false alarm rate than other state-of-the-art classifiers.

Download Full-text