• Convergence Security Journal
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• v.16 no.5
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• pp.33-40
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• 2016

Credit card is means of payment used like cash in terms of function and its users have increased consistently. With development of Internet and electronic commerce a role as payment method of credit card has been growing. But as the risk which results from centralized information and online increases, credit card fraud is also growing. Card theft and loss are decreasing due to countermeasure of card companies and financial supervisory authorities, while card forge and identity theft are increasing. Recently because of frequent personal information leakage and deregulation of financial security following easy-to-use payment enforcement, customer's anxiety about card fraud is growing. And the increase of card fraud lowers trust on credit system as well as causes social costs. In this paper, the security problems of card operating system are addressed in depth and the measures such as immediate switch to IC card terminals, introduction of new security technology, supervision reinforcement of the authorities are proposed.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.31-40
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• 2021

The increasing number of credit card fraud cases has become a considerable problem since the past decades. This phenomenon is due to the expansion of new technologies, including the increased popularity and volume of online banking transactions and e-commerce. In order to address the problem of credit card fraud detection, a rule-based approach has been widely utilized to detect and guard against fraudulent activities. However, it requires huge computational power and high complexity in defining and building the rule base for pattern matching, in order to precisely identifying the fraud patterns. In addition, it does not come with intelligence and ability in predicting or analysing transaction data in looking for new fraud patterns and strategies. As such, Data Mining and Machine Learning algorithms are proposed to overcome the shortcomings in this paper. The aim of this paper is to highlight the important techniques and methodologies that are employed in fraud detection, while at the same time focusing on the existing literature. Methods such as Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), naïve Bayesian, k-Nearest Neighbour (k-NN), Decision Tree and Frequent Pattern Mining algorithms are reviewed and evaluated for their performance in detecting fraudulent transaction.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.68-98
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• 2004

Although the internet is useful for transferring information, Internet auction environments make fraud more attractive to offenders because the chance of detection and punishment are decreased. One of fraud is phantom transaction which is a colluding transaction by the buyer and seller to commit illegal discounting of credit card. They pretend to fulfill the transaction paid by credit card, without actual selling products, and the seller receives cash from credit card corporations. Then seller lends it out buyer with quite high interest rate whose credit score is so bad that he cannot borrow money from anywhere. The purpose of this study is to empirically investigate the factors to detect of the phantom transaction in online auction. Based up on the studies that explored behaviors of buyers and sellers in online auction, bidding numbers, bid increments, sellers' credit, auction length, and starting bids were suggested as independent variables. We developed an Internet-based data collection software agent and collect data on transactions of notebook computers each of which winning bid was over 1,000,000 won. Data analysis with logistic regression model revealed that starting bids, sellers' credit, and auction length were significant in detecting the phantom transaction.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.400-405
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• 2001

This paper addresses an effective approach of training neural networks classifiers for credit card fraud detection. The proposed approach uses evolutionary programming to trails the neural networks classifiers based on maximization of the detection rate of fraudulent usages on some ranges of the rejection rate, loot minimization of mean square error(MSE) that Is a common criterion for neural networks learning. This approach enables us to get classifier of satisfactory performance and to offer a directive method of handling various conditions and performance measures that are required for real fraud detection applications in the classifier training step. The experimental results on "real"credit card transaction data indicate that the proposed classifiers produces classifiers of high quality in terms of a relative profit as well as detection rate and efficiency.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.147-156
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• 2012

Most people in our society use credit card instead of cash or check, so credit card is very important economic method. Credit card supposed to be safe, but hackers hack credit card for illegal deal. Also hackers make fake credit card and issue fake credit card to other people. In this thesis it will study and analyze damage case for safe credit card deal. It will use safe credit card system to insert variety of information and data of using pattern in artificial intelligence network, so print out the possibility of risk and monitor the risk of credit card user's deal pattern, so if one of user's pattern is different than normal pattern, it will pop up message in consultant's screen. This thesis will study and suggest way of prevent from illegal deal and user friendly credit card checking system.

• Journal of Computing Science and Engineering
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• v.5 no.1
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• pp.51-70
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• 2011

This paper introduces a new credit card payment scheme called No Number Credit Card that can significantly reduce the possibility of credit card fraud. The proposed payment system is loosely based on Kerberos, a cryptographic framework that has stood the test of time. In No Number Credit Card, instead of card numbers, only payment tokens are exchanged between the customers and merchants. The tokens are generated based on the payment amount, payment type, client information, and merchant information. However, it does not contain the credit card number, so the merchant or a database hacker cannot acquire and illegally use any credit card numbers. The No Number Credit Card system is ideal for online e-commerce transactions and can be used with any credit card that users possess. It can be used with minor modifications to the current card payment system. We provide the principles of its operation through scenario analysis, a sample implementation, and a security analysis

• Proceedings of the CALSEC Conference
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• 2004.02a
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• pp.75-82
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• 2004

Recently introduced by the major credit card associations as replacements for the decommissioned SET and 3DSET protocols, the new payment models, 3DSecure and UCAF/SPA, have been designed to provide online merchants with a solution to an existing problem in online credit card transactions - the lack of an effective and efficient means of authenticating cardholders. The expected benefits arising from this added level of security from the merchant′s perspective are increased consumer confidence, significant reduction in the levels of fraud and charge backs and "liability shift". Using data gleaned from preliminary interviews, discussion forums and promotional material, we present a critical analysis of the potential barriers and facilitators that will impact on the widespread traction of these programs in the marketplace in the coming years.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1864-1876
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• 2016

Card-Not-Present (CNP) transactions taking place remotely over the Internet are becoming more prevalent. Cardholder authentication should be provided to prevent the CNP fraud resulting from the theft of stored credit card numbers. To address the security problems associated with CNP transactions, the use of a virtual card number derived from the transaction details for the payment has been proposed, instead of the real card number. Since all of the virtual card number schemes proposed so far are based on a password shared between the cardholder and card issuer, transaction disputes due to the malicious behavior of one of the parties involved in the transaction cannot be resolved. In this paper, a new virtual card number scheme is proposed, which is associated with the cardholder's public key for signature verification. It provides strong cardholder authentication and non-repudiation of the transaction without deploying a public-key infrastructure, so that the transaction dispute can be easily resolved. The proposed scheme is analyzed in terms of its security and usability, and compared with the previously proposed schemes.

• Korean Management Science Review
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• v.21 no.2
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• pp.273-289
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• 2004

Although the Internet is useful for transferring information, Internet auction environments make fraud more attractive to offenders, because the chance of detection and punishment is decreased. One of these frauds is the phantom transaction, which is a colluding transaction by the buyer and seller to commit the illegal discounting of a credit card. They pretend to fulfill the transaction paid by credit card, without actually selling products, and the seller receives cash from the credit card corporations. Then the seller lends it out with quite a high interest rate to the buyer, whose credit rating is so poor that he cannot borrow money from anywhere else. The purpose of this study is to empirically investigate the factors necessary to detect phantom transactions in an online auction. Based upon studies that have explored the behaviors of buyers and sellers in online auctions, the following have been suggested as independent variables: bidding numbers, bid increments, sellers' credit, auction lengths, and starting bids. In this study. we developed Internet-based data collection software and collected data on transactions of notebook computers, each of which had a winning bid of over W one million. Data analysis with a logistic regression model revealed that starting bids, sellers' credit, and auction length were significant in detecting the phantom transactions.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.5
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• pp.25-32
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• 2004

An anti-fraud system that utilizes association rules of fraud as well as AFS (Anti Fraud System) for credit card payments in e-commerce is proposed. The association rules are found by applying the data mining algorithm to millions of transaction records that have been generated as a result of orders on goods through the Internet. When a customer begins to process an order by using transaction components of a secure messaging protocol, the degree of risk for the transaction is assessed by using the found rules. More credit information will be requested or the transaction is rejected if it is interpreted as risky.