• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.185-190
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• 2003

Due to the rapid growth of Internet, means of communication with customers in a traditional customer support environment such as telephone calls are being replaced by mainly e-mail in a Web-based customer support system. Although such a Web-based support is efficient and promises potential benefits for firms, including reduced transaction costs, reduced time, and high quality of support, there are some difficulties associated with responding to many types of customer’s inbound e-mails appropriately .As many types of e-mail are received, considerable attention is being paid to methods for increasing the efficiency of managing and responding e-mails. This research proposes an intelligent system for managing customer’s inbound e-mails in organizations by applying case based reasoning technique for responding to various customers' inbound e-mails more effectively. In this approach, a case is represented as a frame-typed data structure corresponding to an inbound e-mail, keywords, and its reply e-mail. In the retrieval procedure, keywords and affinity set is developed to index a case, and then the case is represented as a vector, a case vector. Also, cosines value is calculated to measure the similarity between a new inbound e-mail and the cases in the case base. In the adaptation procedure, we provide several adaptation strategies to adapt and modify the retrieved case. The strategies guide to make an outbound e-mail using product databases, databases for customer support, etc. Additionally, the Web-based system architecture is proposed to implement our methodology. The proposed methodology and system will be helpful for developing more efficient Web-based customer support.

• Journal of Internet Computing and Services
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• v.7 no.2
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• pp.161-172
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• 2006

As the innovative technologies related to ubiquitous computing are being rapidly developed in recent IT trend, the concern for IT dysfunction(e.g., personal information abuse, information risk, threat, vulnerability, etc.) are also increasing. In our study, we suggested how to design and implement to multiple schemes for strong authentication mechanism in real system environments. We introduce the systematic and secure authentication technologies that resolve the threats incurring from the abuse and illegal duplication of financial transaction card in the public and financial institutions. The multiple schemes for strong authentication mechanism applied to java technology, so various application programs can be embedded, Independent of different platforms, to the smartcard by applying the consolidated authentication technologies based on encryption and biometrics(e.g., finger print identification). We also introduce the appropriate guidelines which can be easily implemented by the system developer and utilized from the software engineering standpoint of view. Further, we proposed ways to utilize java card based biometrics by developing and applying the 'smartcard class library' in order for the developer and engineers involved in real system environment(Secure entrance system) to easily understand the program. Lastly, we briefly introduced the potential for its future business application.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3627-3641
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• 2021

Fintech, which stands for financial technology, is growing fast globally since the economic crisis hit the United States in 2008. Fintech companies are striving to secure a competitive advantage over existing financial services by providing efficient financial services utilizing the latest technologies. Fintech companies can be classified into several areas according to their business solutions. Among the Fintech sector, peer-to-peer (P2P) lending companies are leading the domestic Fintech industry. P2P lending is a method of lending funds directly to individuals or businesses without an official financial institution participating as an intermediary in the transaction. The rapid growth of P2P lending companies has now reached a level that threatens secondary financial markets. However, as the growth rate increases, so does the potential risk factor. In addition to government laws to protect and regulate P2P lending, further measures to reduce the risk of P2P lending accidents have yet to keep up with the pace of market growth. Since most P2P lenders do not implement their own credit rating system, they rely on personal credit scores provided by credit rating agencies such as the NICE credit information service in Korea. However, it is hard for P2P lending companies to figure out the intentional loan default of the borrower since most borrowers' credit scores are not excellent. This study analyzed the voices of telephone conversation between the loan consultant and the borrower in order to verify if it is applicable to determine the personal credit score. Experimental results show that the change in pitch frequency and change in voice pitch frequency can be reliably identified, and this difference can be used to predict the loan defaults or use it to determine the underlying default risk. It has also been shown that parameters extracted from sample voice data can be used as a determinant for classifying the level of personal credit ratings.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.49-57
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• 2021

With the advent of the era of the fourth industry, more and more scientific techniques are being used to solve decision-making problems. In particular, big data analysis technology is developing as it becomes easier to collect numerical data. Therefore, in this study, in order to overcome the limitations of qualitatively analyzing investment trends, the association of various products was analyzed using associated analysis techniques. For the experiment, two experimental periods were divided based on the COVID-19 economic crisis, and sales information from individuals, institutions, and foreign investors was collected, and related analysis algorithms were implemented through r software. As a result of the experiment, institutions and foreigners recently invested in the KOSPI and KOSDAQ markets and bought futures and products such as ETF. Individuals purchased ETN and ETF products together, which is presumed to be the result of the recent great interest in sector investment. In addition, after COVID-19, all investors tended to be passive in investing in high-risk products of futures and options. This paper is thought to be a useful reference for product sales and product design in the financial field.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.215-220
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• 2019

The block chain technology is a technique that prevents manipulation of data and ensures integrity and reliability. Ethereum is building a smart contract environment as a type of encryptionenabled system based on block chains. Smart contracts can be implemented when conditions are met, thus increasing confidence in digital data. However, smart contracts that are being tried in various ways are not covered by information security and personal information protection. The structure in which the network participant can view the open transaction ledger is exposed to data or personal information listed in the block chain. In this study, it is possible to manage the data of personal information recorded in the block chain directly. This study is protected personal information by preventing the exposure of personal information and by executing time code, it is possible to erase recorded information after a certain period of time has elapsed. Based on the proposed system in the future, it is necessary to study the additional management techniques of unknown code defects or personal information protection.

• Journal of IKEEE
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• v.23 no.2
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• pp.508-516
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• 2019

Smart home with various IoT devices provides convenient and efficient services. However, security is important because sensitive information such as private video and audio can be collected and processed, as well as shared over the Internet. To manage such smart home IoT devices, we use blockchain technology that provides data integrity and secure management. In this paper, we utilize a PoS(Proof of Stake) method that verifies the block through the accumulated stake in the network rather than the computation power, out of the PoW(Proof of Work) block chain, in which the computation for the existing verification must be continuously performed. Among them, we propose a blockchain based system with DPoS(Delegated Proof of Stake) method to actively solve the scalability part, for security that is suitable for smart home IoT environment. We implement the proposed system with DPoS based EOSIO to show realization, and we show performance improvement in terms of transaction processing speed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.69-77
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• 2019

As information technology advances, the penetration of smart devices connected to the Internet, such as smart phone and tablet PC, has rapidly expanded, and as sensor prices have fallen the Internet of Things has begun to be introduced in the industry. Today's industry is rapidly changing and evolving, requiring companies to respond to the new paradigm of business. In this situation, companies need to actively manage and maintain customer relationships in order to acquire loyal customers who bring them a high return. The purpose of this study is to suggest a method to manage customer relationship using real time IoT data including IoT product usage data, customer characteristics and transaction data. This study proposes a method of segmenting customers through RFM analysis and transition index analysis. In addition, a real-time monitoring through control charts is used to identify abnormalities in product use and suggest ways of differentiating marketing for each group. In the study, 44 samples were classified as 9 churn customers, 10 potential customers, and 25 active customers. This study suggested ways to induce active customers by providing after-sales benefit for product reuse to a group of churn customers and to promote the advantages or necessity of using the product by setting the goal of increasing the frequency of use to a group of potential customers. Finally, since the active customer group is a loyal customer, this study proposed an one-on-one marketing to improve product satisfaction.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.4
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• pp.97-110
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• 2022

The purpose of this study is to analyze the level of public data convergence capabilities of administrative organizations and to explore important variables in data-based organizational capabilities. The theoretical background was summarized on public data and use activation, joint use, convergence, administrative organization, and convergence constraints. These contents were explained Public Data Act, the Electronic Government Act, and the Data-Based Administrative Act. The research model was set as the data-based organizational capabilities effect by a data-based administrative capability, public data operation capabilities, and public data operation constraints. It was also set whether there is a capabilities difference data-based on an organizational operation by the level of data convergence capabilities. This study analysis was conducted with hierarchical cluster analysis and multiple regression analysis. As the research result, First, hierarchical cluster analysis was classified into three groups. It was classified into a group that uses only public data and structured data, a group that uses public data on both structured and unstructured data, and a group that uses both public and private data. Second, the critical variables of data-based organizational operation capabilities were found in the data-based administrative planning and administrative technology, the supervisory organizations and technical systems by public data convergence, and the data sharing and market transaction constraints. Finally, the essential independent variables on data-based organizational competencies differ by group. This study contributed. As a theoretical implication, this research is updated on management information systems by explaining the Public Data Act, the Electronic Government Act, and the Data-Based Administrative Act. As a practical implication, the activity reinforcement of public data should be promoting the establishment of data standardization and search convenience and elimination of the lukewarm attitudes and Selfishness behavior for data sharing.

• Journal of Industrial Convergence
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• v.20 no.11
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• pp.191-196
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• 2022

In the fintech field, financial transactions with smart phones are actively conducted. User authentication technology is essential for safe financial transactions. PIN authentication through the existing security keypads is convenient to input but has weaknesses in security and others. The biometric authentication technique is secure, but there is a possibility of false positive and false negative authentication. To compensate for this, two-factor authentication is used. In this paper, we propose the 1.5-factor authentication that can increase convenience and security through PIN input with biometric authentication. It provides the stability of fingerprint authentication and convenience of two or three PIN inputs, and this makes safe financial transaction possible. Since biometric authentication is performed at the same time when entering PIN, while security is required by applying fingerprint authentication to the area touched while entering PIN. The User authentication is performed while ensuring convenience to input through additional PIN input in situations where high safety is required, and Safe financial transactions are possible.

• Journal of Information Technology Services
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• v.22 no.2
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• pp.71-92
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• 2023

Globally, under the leadership of advanced ICT countries, the private sector is promoting various policies to promote the digital transformation of public services. Looking at the research trend, design of public service indicators, development of evaluation system, and empirical research are being carried out steadily, but there are insufficient research cases on models in which the private sector participates in the planning, development, and operation of public services. In this study, Private-centric digital public service suitability evaluation indicators were discovered through interviews with experts in various fields, and weights for each indicator were analyzed through AHP evaluation. In addition, by applying the analysis results to 18 digital public services on a trial basis, the importance and priority of evaluation indicators for each service were derived, and at the same time, the evaluation framework was designed and applied to diagnose implications. As a result of the study, 'social utility', 'corporate acceptability', and 'public acceptability' were selected as the top three indicators of suitability evaluation. At this time, it was analyzed that the weight of the 'company acceptability' index, which includes sub-indices such as 'service profitability', 'service scalability', and 'private initiative possibility', was the highest among the three top indicators. As a result of the demonstration for public services, "IoT facility unmanned remote monitoring service", "blockchain real estate transaction service", and "digital twin disaster prediction service" were evaluated as the most suitable public services for the transition to the private sector.