• Journal of Intelligence and Information Systems
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• v.12 no.3
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• pp.1-13
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• 2006

Ubiquitous computing is a study area explained in a myriad of contexts and technological terms. Payment, however, refers in nature to an act of money transfer from one entity to another, and it is obvious that a payment method will be valued as long as the transaction can be completed with safety no matter what technology was used. The key to U-payment is convenience and security in the transfer of financial information. The purpose of this paper is to find a desirable U-payment scheme by looking at the characteristics of seamlessness under the ubiquitous environments, strong personal device, and peer-based information transactions. We also propose U-SDT Protocol integrating technologies such as Radio Frequency Identification (RFID), Bluetooth, Personal Payment Device, Account Managing Application and Transaction ID as a way to make transactions between users seamless and secure better privacy protection.

• Korean Journal of Construction Engineering and Management
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• v.20 no.5
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• pp.115-124
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• 2019

The purpose of this study is to analyze the housing price variation within the redevelopment project district, affected by the characteristics of project and implementation stage. This study implemented the hedonic price model employing the actual transaction price with 24 dependent variables from 2006 to 2016 inside 19 redevelopment districts in Seoul. Research finding indicates that the larger ratio of the number of tenants and general distribution, the smaller ratio of rented households and the more positive effect of housing price. It is noteworthy that this study demonstrated the actual transaction price of houses located within the project districts by implementation stage. This study is expected to help the policy makers, the developers and the investors make more reliable decisions on the feasibility study related to the redevelopment project.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.6
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• pp.67-81
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• 2010

As wide propagation of smartphones, e-commerce with smartphones increases rapidly. Such as transfer or stock trade systems. It has prospect that most of financial companies going to offer e-commerce systems via smartphones. And e-commerce via smartphones will be increased, hence the nature of smartphone that can be used whenever, wherever. However, legislation of e-commerce in Korea does not reflect these characteristics of smartphones, because it has set standards in regular PC. So that this study is security threat and feature of smartphones considering that the current legal system will use Certificate constraints, ensuring the safety of e-commerce and install security programs for protection of users, e-commerce responsible for the accident analysis has focused on the issues presented for this improvement.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.173-182
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• 2022

In this paper, we propose a machine learning model that can prevent fraudulent transactions in advance and interpret them using the XAI approach. For the experiment, we collected a real data set of 12,258 mobile phone sales posts from Joonggonara, a major domestic online C2C resale trading platform. Characteristics of the text corresponding to the post body were extracted using Doc2vec, dimensionality was reduced through PCA, and various derived variables were created based on previous research. To mitigate the data imbalance problem in the preprocessing stage, a complex sampling method that combines oversampling and undersampling was applied. Then, various machine learning models were built to detect fraudulent postings. As a result of the analysis, LightGBM showed the best performance compared to other machine learning models. And as a result of SHAP, if the price is unreasonably low compared to the market price and if there is no indication of the transaction area, there was a high probability that it was a fraudulent post. Also, high price, no safe transaction, the more the courier transaction, and the higher the ratio of 0 in the price also led to fraud.

• Journal of Internet of Things and Convergence
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• v.8 no.1
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• pp.11-16
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• 2022

Efforts to incorporate blockchain into various fields are continuing as cryptocurrency transactions become more active. Blockchain has the characteristic that once recorded facts cannot be modified or deleted. Due to these characteristics, the use in the field of recording and proving certain facts, such as voting or proof of ownership, is attracting attention. In this paper, users who want to participate in the transaction process using private blockchain, one of the types of blockchain, are divided into real estate brokers, building owners, and purchasers (lessors), and roles are assigned to each user. In addition, we would like to propose a system to increase reliability through the participation of institutions. Through this, we intend to not only present a real estate transaction system that prevents damage from real estate fraud related to false sales and fraudulent contracts, but also enhances reliability and contributes to finding ways to utilize blockchain in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1986-2009
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• 2024

The integration of blockchain technology with the rapid growth of Internet of Things (IoT) devices has enabled secure and decentralised data exchange. However, security vulnerabilities and performance limitations remain significant challenges in IoT blockchain networks. This work proposes a novel approach that combines transaction representation and machine learning techniques to address these challenges. Various clustering techniques, including k-means, DBSCAN, Gaussian Mixture Models (GMM), and Hierarchical clustering, were employed to effectively group unlabelled transaction data based on their intrinsic characteristics. Anomaly transaction prediction models based on classifiers were then developed using the labelled data. Performance metrics such as accuracy, precision, recall, and F1-measure were used to identify the minority class representing specious transactions or security threats. The classifiers were also evaluated on their performance using balanced and unbalanced data. Compared to unbalanced data, balanced data resulted in an overall average improvement of approximately 15.85% in accuracy, 88.76% in precision, 60% in recall, and 74.36% in F1-score. This demonstrates the effectiveness of each classifier as a robust classifier with consistently better predictive performance across various evaluation metrics. Moreover, the k-means and GMM clustering techniques outperformed other techniques in identifying security threats, underscoring the importance of appropriate feature selection and clustering methods. The findings have practical implications for reinforcing security and efficiency in real-world IoT blockchain networks, paving the way for future investigations and advancements.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.5-20
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• 2018

This paper aims to analyze characteristic by the cities focused on the ratio of new apartment resale that is one of the apartment unit sale market, which has been increased recently. So, this study examined characteristics of population, apartment trade & sale, housing with 162 cities and counties and performed multiple regression analysis with dependent variable, ratio of new apartment resale. As a result. the factors affecting the ratio of new apartment resale are 7variables, apartment sales rate, transfer of ownership, apartment turnover rate, sale volume, regional apartment rate, population increasing rate, housing average apartment sale price rate. In terms of the increase in apartment sales prices, the rate of sales price increase was relatively low in areas where the transaction rate for apartment sales is high, and the number of apartment sales right transactions increased as the number of other ownership transfers rose. As a result, the data will be based on the improvement of the government's policies and systems to stimulate the transaction focused on the real estate agents in the apartment market.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.55-66
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• 2023

This study analyzes the characteristics of customer's preferences on banking channels (branches, automated machines, telebanking, internet banking, and mobile banking) and examines the factors influencing channel usage. To accomplish this, ANOVA and multiple regression analysis are performed using customer data from Bank A. The analysis reveals that customers primarily utilizing branch counter transactions have a significant impact on the profitability of 1st and 2nd grade banks, particularly among the age group of 50 years and above. Additionally, it is observed that as customers' loan, deposit, and financial product holdings increase, branch counter transactions also increase. On the other hand, it is found that as the usage of mobile banking decreases in terms of loans and deposits, transaction volume increases.

• Economic and Environmental Geology
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• v.57 no.4
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• pp.431-447
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• 2024

This study aims to analyze the supply and demand trends and regional distribution characteristics of the stone industry through transaction records of the domestic natural stone market. The demand for natural stone is increasing globally, but domestic stone producers are facing financial difficulties due to the influx of low-cost stone, and the government is implementing various support policies, such as mandating the use of domestic stone. However, the influx of low-cost stones has led to management deterioration for domestic stone producers, prompting the government to implement various support policies such as mandating the use of domestic stones. An analysis of the natural stone transaction records from the Public Procurement Service revealed that granite was the main type of rock. The main trading items were natural stone curbs and natural stone slabs, with an average annual transaction amount of approximately 312.8 billion KRW from 2017 to 2021. A comparison of the stone distribution status between the metropolitan area and non-metropolitan areas showed that the metropolitan area had high demand, while non-metropolitan areas served as major supply sources. Cities such as Pocheon in Gyeonggi-do, Iksan in Jeollabuk-do, and Geochang in Gyeongsangnam-do play important roles as major stone suppliers. Based on these results, this study proposes fostering the stone industry tailored to regional characteristics, diversifying distribution channels, and establishing a sustainable supply chain for the sustainable development of the stone industry. Additionally, it emphasizes the need for close cooperation and support among the government, industry, and research institutions.

• Journal of Global Scholars of Marketing Science
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• v.7
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• pp.321-337
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• 2001

The Purpose of this study is to empirically examine the factors that affect the consumer's buying behavior under the e-commerce environment. In order to achieve this goal, vendor characteristics, securities of transaction, concern for privacy, shopping orientation and perceived channel utilities were used as independent variables. Findings of study indicated that the concerns for abusing individual information, perceived securities of transaction, consumer's recreational orientation, consumer's convenience orientation, perceived distribution channel are the robust predictors of buying behavior of internet users.