• The Journal of Economics, Marketing and Management
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• v.9 no.5
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• pp.39-50
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• 2021

Purpose: This study is to analyze the changes of consumption patterns to diagnose the economic impacts on consumers' market during COVID-19, and to suggest implications to overcome the new social and economic crisis of Jeju Island. Research design, data, and methodology: We collected a set of credit card transaction records issued by BC Card Company from merchants in Jeju Special Self-Governing Province for past 4 years from 2017 to 2020 from the Jeju Data Hub run by Jeju Special Self-Governing Province. The big data contains details of approved credit card transactions including the approval numbers, amount, locations and types of merchants, time and age of users, etc. The researchers summed up amount in monthly basis, transforming big data to small data to analyze the changes of consumption before and after COVID-19. Results: Sales fell sharply in transportation industries including airlines, and overall consumption by age group decreased while the decrease in consumption among the seniors was relatively small. The sales of Yeon-dong and Yongdam-dong in Jeju City also fell significantly compared to other regions. As a result of the paired t-test of all 73 samples in Jeju City, the p-value of the mean consumption of the credit card in 2019 and 2020 is significant, statistically proven that the total consumption amount in the two years is different. Conclusions: We found there are sensitive spots that can be strategically approached based on the changes in consumption patterns by industry, region, and age although most of companies and small businesses have been hit by COVID-19. It is necessary for local companies and for the government to be focusing their support on upgrading services, in order to prevent declining sales and job instability for their employees, creating strategies to retain jobs and prevent customer churn in the face of the crisis. As Jeju Province is highly dependent on the tertiary industry, including tourism, it is suggested to create various strategies to overcome the crisis of the pandemic by constantly monitoring the sales trends of local companies.

• The Journal of Information Technology
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• v.4 no.4
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• pp.113-128
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• 2001

The international trade industry is on the brink of a radical Internet-driven transformation. TradeCard is a payment and settlement system that is an alternative to letters of crdeit. That is, TradeCard is a business-to-business e-commerce infrastructure that enables buyers and sellers to conduct and settle international trade transactions securely over the Internet. Paperless, payment-guaranteed international trade transactions - which eliminate the traditional letters of credit with electronic certifications - are widely considered the most difficult B2B transactions to conduct. The TradeCard system was initially built to accommodate and process this complex, cross-border payment type at a US$100 service fee for each transaction of up to US$100,000 since November 1999.

• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.49-52
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• 2004

M-Commerce에서 안전한 서비스를 제공하기 위해서는 보안 기능을 갖춘 결제 솔루션이 필수적이다. M-Commerce를 이응하기 위한 사용자의 이동 단말기는 핸드폰, PDA, 스마트폰 등으로 다양화 되어가고 있으며, 이 중에서도 PDA의 인터페이스와 이동 접속은 기존 핸드폰의 유선 인터넷의 정보 의존도가 높은 단점을 극복할 수 있다. 본 논문에서는 타원곡선 암호를 이용하여 PDA 기반의 신용카드 결제 시스템을 설계하였다. 제안된 시스템의 SECURE CARD 모듈은 PDA 단말기 자체에 개인정보, 배송정보, 카드정보를 암호화하여 안전하게 저장함으로써 단말기의 정보입력시에 필요한 불편함을 제거하였다. 또한 프로토콜은 M-Commerce에서 인증, 기밀성, 무결성, 부인봉쇄 서비스 둥의 보안기능을 제공하도록 설계되었다.

• Proceedings of the KAIS Fall Conference
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• 2001.11a
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• pp.230-235
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• 2001

SET(Secure Electronic Transaction)은 인터네트와 같은 open network에서 안전하게 상거래를 할 수 있도록 보장해주는 지불 프로토롤이다. SET은 보안상의 허점을 보완하고자 신용카드 회사인 비자, 마스터카드와 IBM, 넷스케이프, 마이크로소프트 그리고 VeriSign의 기술적인 도움으로 개발되었다. SET은 RSA 데이터 보안회사의 암호화 기술에 기초를 두고 있으며, 기술사양 자체가 공개이므로 누구나 자유롭게 SET 프로토롤을 사용하는 소프트웨어를 개발 할 수 있다. SET은 우리가 일상생활에서 이용하는 신용카드 거래체계를 인터네트를 통한 전자상거래에서도 유사하게 이용할 수 있도록 하였다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1525-1540
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• 2015

Due to a rapid advancement in the electronic commerce technology, the payment method varies from cash to electronic settlement such as credit card, mobile payment and mobile application card. Therefore, financial fraud is increasing notably for a purpose of personal gain. In response, financial companies are building the FDS (Fraud Detection System) to protect consumers from fraudulent transactions. The one of the goals of FDS is identifying the fraudulent transaction with high accuracy by analyzing transaction data and personal information in real-time. Data mining techniques are providing great aid in financial accounting fraud detection, so it have been applied most extensively to provide primary solutions to the problems. In this paper, we try to provide an overview of the research on data mining based fraud detection. Also, we classify researches under few criteria such as data set, data mining algorithm and viewpoint of research.

• Smart Media Journal
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• v.12 no.5
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• pp.9-16
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• 2023

In the recommendation system of the credit card company, it is necessary to understand the customer patterns to predict a customer's next merchant based on their histories. The data we want to model is much more complex and there are various patterns that customers choose. In such a situation, it is necessary to use an effective model that not only shows the relevance of the merchants, but also the relevance of the customers relative to these merchants. The proposed model aims to predict the next merchant for the customer. To improve prediction performance, we propose a novel model, called Customer-based Recommendation Model (CRM), to produce a more efficient representation of customers. For the next merchant recommendation system, we use a synthetic credit card usage dataset, BC'17. To demonstrate the applicability of the proposed model, we also apply it to the next item recommendation with another real-world transaction dataset, IJCAI'16.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.225-231
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• 2010

Transaction value of business-to-business(B2B) is composed of various factors for groups and time series. In this paper, we use the panel data for finding various variables and using this we analyse the factors that is major influence to transaction value of business-to-business. For analysis we looked at transaction value of business-to-business of 7 groups such as manufacturing industry, electric, gas and piped water industry, construction industry, retail & wholesale trade, traffic industry, publish, image; broad-casting & telecommunication and information service industry, etc. In our analysis we looked at the transaction value of business-to-business during the period from 2005.01 to 2009.12. We examined the data in relation to the transaction value of cyber shopping mall, company bond, composite stock price index, transaction value of credit card, loaned rate of interest in deposit bank, rate of exchange looking at the factors which determine the transaction value of business-to-business, evidence was produced supporting the hypothesis that there is a significant positive relationship between the transaction value of cyber shopping mall, composite stock price index and loaned rate of interest in deposit bank, rate of exchange. The company bond is negative relationship, transaction value of credit card is positive relationship and they are not significant variables in terms of the transaction value of business-to-business.

• International Journal of Internet, Broadcasting and Communication
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• v.8 no.1
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• pp.7-18
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• 2016

Several authentication methods have been developed to make use of tokens in the mobile networks and smart payment systems. Token used in smart payment system is genearated in place of Primary Account Number. The use of token in each payment transaction is advantageous because the token authentication prevents enemy from intercepting credit card number over the network. Existing token authentication methods work together with the cryptogram, which is computed using the shared key that is provisioned by the token service provider. Long lifetime and repeated use of shared key cause potential brawback related to its vulnerability against the brute-force attack. This paper proposes a per-transaction shared key mechanism, where the per-transaction key is agreed between the mobile device and token service provider for each smart payment transaction. From server viewpoint, per-transaction key list is easy to handle because the per-transaction key has short lifetime below a couple of seconds and the server does not need to maintain the state for the mobile device. We analyze the optimum size of the per-transaction shared key which satisfy the requirements for transaction latency and security strength for secure payment transactions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.117-122
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• 2009

In these days, world economic crisis is getting worse and most of us are having difficulties in handling financial balance. By noticing that credit card is the most important payment method of individuals, we developed e-receipt system, which helps a person easily keep track of credit card spendings by showing purchase and transaction details in real-time. We've used embedded software engineering techniques in developing the e-receipt system. The system we developed here will benefit most of us by preventing over-spending of credit cards and will lead to healthy spending habits.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.200-206
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• 2021

Fraud in e-commerce transaction increased in the last decade especially with the increasing number of online stores and the lockdown that forced more people to pay for services and groceries online using their credit card. Several machine learning methods were proposed to detect fraudulent transaction. Neural networks showed promising results, but it has some few drawbacks that can be overcome using optimization methods. There are two categories of learning optimization methods, first-order methods which utilizes gradient information to construct the next training iteration whereas, and second-order methods which derivatives use Hessian to calculate the iteration based on the optimization trajectory. There also some training refinements procedures that aims to potentially enhance the original accuracy while possibly reduce the model size. This paper investigate the performance of several NN models in detecting fraud in e-commerce transaction. The backpropagation model which is classified as first learning algorithm achieved the best accuracy 96% among all the models.