• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.1
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• pp.187-198
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• 2018

Recently, financial transactions and electronic commerce in cyberspace are being performed more quickly and conveniently, with the development in diverse types of fintech and biometric authentication. But user authentication using passwords still occupies a big proportion even in these new services. therefore, safe creation and management of passwords is fundamental and indispensable to protect personal information and asset. This study examined the patterns of password usage by conducting a survey and analyzed factors influencing password security behavior intentions using the heath belief model. As a result, perceived susceptibility, perceived severity, perceived benefits, and perceived barriers significantly affected security behavior intentions, and especially, perceived severity had a moderating effect in other factors.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.21-32
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• 2021

Due to the recent development in electronic financial services, transactions of electronic prepayment are rapidly increasing. The increased transactions of electronic prepayment, however, also leads to the increased fraud attempts. It is mainly because electronic prepayment can easily be converted into cash. The objective of this paper is to develop a methodology that can effectively detect fraud transactions in electronic prepayment, by using sequential pattern mining techniques. To validate our approach, experiments on real transaction data were conducted and the applicability of the proposed method was demonstrated. As a result, the accuracy of the proposed method has been 95.6 percent, showing that the proposed method can effectively detect fraud transactions. The proposed method could be used to reduce the damage caused by the fraud attempts of electronic prepayment.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.365-385
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• 2022

The easy payment service is a payment and remittance service that uses a simple authentication method. As online transactions have increased due to COVID-19, the use of an easy payment service is increasing. At the same time, electronic financial industries such as Naver Pay, Kakao Pay, and Toss are diversifying the competition structure of the easy payment market; meanwhile overseas fintech companies PayPal and Alibaba have a unique market share in their own countries, while competition is intensifying in the domestic easy payment market, as there is no unique market share. In this study, the participants in the easy payment market were classified as electronic financial companies, mobile phone manufacturers, and financial companies, and a SWOT analysis was conducted on the representative services in each industry. The analysis examined the user reviews of Google Play Store via a topic modeling analysis, and it employed positive topics as strengths and negative topics as weaknesses. In addition, topic modeling was conducted by dividing news articles into political, economic, social, and technology (PEST) articles to derive the opportunities and threats to easy payment services. Through this research, we intend to confirm the service capabilities of easy payment companies and propose a service activation strategy that allows gaining the upper hand in the market.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.65-77
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• 2022

Due to the recent development in electronic financial services, transactions of electronic prepayment are rapidly growing, leading to growing fraud attempts. This paper proposes a methodology that can effectively detect fraud transactions in electronic prepayment by machine learning algorithms, including support vector machines, decision trees, and artificial neural networks. Actual transaction data of electronic prepayment services were collected and preprocessed to extract the most relevant variables from raw data. Two different approaches were explored in the paper. One is a transaction-based approach, and the other is a user ID-based approach. For the transaction-based approach, the first model is primarily based on raw data features, while the second model uses extra features in addition to the first model. The user ID-based approach also used feature engineering to extract and transform the most relevant features. Overall, the user ID-based approach showed a better performance than the transaction-based approach, where the artificial neural networks showed the best performance. The proposed method could be used to reduce the damage caused by financial accidents by detecting and blocking fraud attempts.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.185-194
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• 2018

This study investigates the limitations of blockchain technology and the ways to improve it by using Delphi technique. Limit factors and improvement measures are classified into technology, service, and legal system. First, from a technical point of view, lack of standardization of the technology, insufficiency of integration, lack of scalability, unclear cancellation or correction policy, excessive cost of transaction verification, insufficient personal information protection and not enough to respond to hacking defense were the limiting factors. In order to improve these, the followings; ensuring standardization, securing integration and scalability, establishing cancellation of each applicable data, establishment of correction policy, efficiency of verification cost, the protection of personal information and countermeasure against hacking are provided. The related technology development and countermeasures must be established to effectively introduce the blockchain technology to the market. Second, in the early stage of blockchain service, it showed lack of utilization of the blockchain, security threat, shortage of skilled workers, and lack of legal liability. As a solution to these problems, it is necessary to suggest various applications, against security threat, training professional manpower, and securing legal responsibility. It should also provide a foundation for providing institutionally stable services. Third, from as legal system point of view, inadequate legal compliance, lack of relevant regulation, and uncertainty in the regulation were the limiting factors. Therefore establishing a legal system, which is the most important area for activating the service, should be accompanied by the provision of legal countermeasures, clearness of regulations and measures to be taken by relevant governmental authorities. This study will contribute as a reference for a research, related to the blockchain.

• Journal of the Korean Society of Clothing and Textiles
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• v.40 no.6
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• pp.1045-1061
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• 2016

This study clarifies differences in attitudes toward the Omni-Channel service (Pintech service, Beacon service, and Click and Collect service) and fashion consumption behavior among four clusters grouped by level of technology readiness. An online survey was conducted; 572 individuals between 20 and 30 years of age were collected, but only 539 were used. Factor analysis, cluster analysis, descriptive statistics, ANOVA, and frequency analysis were adopted to analyze data using SPSS 20.0. The results are as follows. Technology readiness was divided into four factors: optimism, innovativeness, discomfort, and insecurity. Participants were divided into four groups according to four sub-factors of technology readiness: brave adopters, optimistic laggards, indifferent adopters, and critical adopters. These groups showed significant differences in attitudes toward the Omni-Channel service and fashion consumption behavior. Critical adopters and brave adopters recognized the value of the Omni-Channel service and had more positive attitudes toward it than other groups. Critical adopters also better perceived the risk of service with new technology that showed higher fashion innovativeness and monthly consumption of fashion products than other groups. We inferred that the indifferent adopters did not use the Omni-Channel service or services offered by fashion retailers as much as other groups because indifferent adopters were less interested in both the Omni-Channel service and fashion consumption behavior than other groups. Optimistic laggards viewed the Omni-Channel service optimistically, despite perceptions of high risks to accompanying it and a low intent to use it. The results of this study assisted in the formation of a theoretical framework of consumer behavior associated with the Omni-Channel, which is an emerging issue in research related to distribution. The results can help fashion industries that operate consumer-oriented marketing based on Omni-Channel strategies.