• Journal of Multimedia Information System
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• v.5 no.2
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• pp.99-104
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• 2018

Phishing website has become a crucial concern in cyber security applications. It is performed by fraudulently deceiving users with the aim of obtaining their sensitive information such as bank account information, credit card, username, and password. The threat has led to huge losses to online retailers, e-business platform, financial institutions, and to name but a few. One way to build anti-phishing detection mechanism is to construct classification algorithm based on machine learning techniques. The objective of this paper is to compare different classifier ensemble approaches, i.e. random forest, rotation forest, gradient boosted machine, and extreme gradient boosting against single classifiers, i.e. decision tree, classification and regression tree, and credal decision tree in the case of website phishing. Area under ROC curve (AUC) is employed as a performance metric, whilst statistical tests are used as baseline indicator of significance evaluation among classifiers. The paper contributes the existing literature on making a benchmark of classifier ensembles for web phishing detection.

• The Journal of Sustainable Design and Educational Environment Research
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• v.21 no.3
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• pp.1-13
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• 2022

This study is a case study to identify the spatial composition and structural problems of existing schools for spatial innovation as a future school that can operate a credit system for old high schools and establish a mid-to-long-term arrangement plan as a credit system operating school capable of various teaching and learning in the future. The study results are as follows: First, most of the problems of the old high schools entailed that there was very poor connectivity between buildings as most of them were arranged in a single, standard design-type unit building and distributed in multiple buildings. In addition, the floor plan of each building is suggested to be a structure in which student exchange and rest functions cannot be achieved during the break period due to the spatial composition of the classroom and hallway concepts. Second, in the direction of the high school space configuration for future school space innovation, the arrangement plan should be established by reflecting the collective arrangement in consideration of the shortening of the movement route and the expansion of subject areas due to the movement of students on the premise of the subject classroom system. Moreover, it is desirable to provide a square-type space for rest and exchange in the central area where communication and exchange are possible according to the moving class. Third, as the evaluation criteria for relocating old high schools, a space program is prepared based on the number of classes in the future, and legal analysis of school land use and land use efficiency analysis considering regional characteristics are conducted. Based on such analysis data, mid-to-long-term land use plans and space arrangement plans for the entire school space such as the school facility complex are established.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.1
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• pp.139-149
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• 2019

The purpose of this study is to contribute to the minimization of the social cost due to the insolvency by improving the success rate of the startups by providing useful information to the founders and the start-up support institutions through analysis of non-financial information affecting the failure of the startups. This study is aimed at entrepreneurs. The entrepreneurs that are defined by the credit guarantee institutions generally refer to entrepreneurs within 5 years of establishment. The data used in the study are sampled from the companies that were supported by the start-up guarantee from January 2014 to December 2013 as the end of December 2017. The total number of sampled firms is 2,826, 2,267 companies (80.2%), and 559 non-performing companies (19.8%). The non-financial information of the entrepreneur was divided into the entrepreneur characteristics information, the entrepreneur characteristics information, the entrepreneur asset information and the entrepreneur 's credit information, and cross-tabulations and logistic regression analysis were conducted. As a result of cross-tabulations, univariate analysis showed that personal credit rating, presence in the industry, presence of residential housing, presence of employees, and presence of financial statements were selected as significant variables. As a result of the logistic regression analysis, three variables such as personal credit rating, occupation in the industry, and presence of residential house were found to be important factors affecting the failure of founding companies. This result shows the importance of entrepreneur 's personal credibility and experience and entrepreneur' s assets in business management. The start-up support institutions should reflect these results in the entrepreneur 's credit evaluation system, and the entrepreneurs need training on the importance of the personal credit and the management plan in the entrepreneurial education. The results of this analysis will contribute to the minimization of the incapacity of startups by providing useful non-financial information to founders and start-up support organizations.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.31-40
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• 2012

Face recognition refers to the process of identifying individuals based on their facial features. It has recently become one of the most popular research areas in the fields of computer vision, machine learning, and pattern recognition because it spans numerous consumer applications, such as access control, surveillance, security, credit-card verification, and criminal identification. However, illumination variation on face generally cause performance degradation of face recognition systems under practical environments. Thus, this paper proposes an novel face recognition system using a fusion approach based on local binary pattern and two-dimensional principal component analysis. To minimize illumination effects, the face image undergoes the local binary pattern operation, and the resultant image are divided into two sub-images. Then, two-dimensional principal component analysis algorithm is separately applied to each sub-images. The individual scores obtained from two sub-images are integrated using a weighted-summation rule, and the fused-score is utilized to classify the unknown user. The performance evaluation of the proposed system was performed using the Yale B database and CMU-PIE database, and the proposed method shows the better recognition results in comparison with existing face recognition techniques.

• Journal of Distribution Science
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• v.14 no.12
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• pp.141-151
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• 2016

Purpose - Salesperson perceptions of the fairness and accuracy of a performance evaluation system were examined by managerial and professional employees of large organization. The performance evaluation process is central to many personal decisions such as attitude for job and sales performance. This study investigates the relationship between perceived evaluation fairness, job satisfaction, organizational commitment, and sales performance. The main purpose of this study is to develop and empirically test a comprehensive model of salespersons' perceived evaluation fairness on sales performance. For this purpose, we identified the structural relationship between perceived evaluation fairness, job satisfaction, organizational commitment, and sales performance. Also we investigate the mediating effects on job satisfaction and organizational commitment between perceived evaluation fairness and sales performance. Research design, data, and methodology - To empirically test these relationships, data were collected by in-depth interviews from sales managers and questionnaire surveys from 300 salespersons who work for sales area (credit card company, insurance company). Demographically, the overall sample was 91.6% female, 77.9% 30s and 40s, and 34% college educated, with an average tenure with their present organizations of 4 years. The questionnaire was composed of total 20 items dealing with frequency, quality, and consequences of perceived evaluation fairness, job satisfaction, organizational commitment, and sales performance. To test the research hypotheses, collected data analyzed by confirmatory factor analysis (CFA) and structure equation model (SEM). Results - Through extensive and rigorous literature review process of related literature(Perceived evaluation fairness, Job satisfaction, Organizational commitment, Sales performance), research model and research hypothesis was set up. This study obtains the following research results. First, perceived evaluation fairness has a positive effect on job satisfaction, whereas the effects of perceived evaluation fairness on organizational commitment and sales performance did not show statistically significant result. Second, job satisfaction and organizational commitment have complete mediating roles to the relationship between perceived evaluation fairness and organizational commitment, and relationship between perceived evaluation fairness and sales performance. Conclusions - Based on the results, salespersons' perceived evaluation fairness is one of the key independent variable for making high job satisfaction, organizational commitment, and sales performance. Finally the theoretical, managerial implication and research limitations are mentioned in the discussion.

• Journal of The Korean Association of Information Education
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• v.25 no.3
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• pp.511-525
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• 2021

The purpose of this study is to develop a design guideline to provide user-friendly experience and convenience for the online support system for the curriculum at primary/secondary schools. To achieve the objective, best practices of overseas on the online support system for curriculum as well as prior research were analyzed. In addition, UX/UI usability problems and needs were derived through a survey of 74 professionals and teachers who are monitoring NCIC and high school credit system sites. Based on the analysis of best practices of overseas and survey results, the draft of the design guideline was derived, and Delphi method was conducted by experts to re- vise the design guidelines and evaluate their validity. This study is meaningful in that it suggests the direction of improvement of the system currently being serviced and the direction of the design of the system to be developed in the future, by providing design guidelines that can be generally applied to online support systems that perform tasks related to the curriculum.

• The Journal of the Korea Contents Association
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• v.5 no.1
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• pp.109-116
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• 2005

This paper is to develop the prototype of a decision making for loan granting system at banks and to evaluate the effectiveness of it. The prototype is called at FENET-LG in this paper. The decision to grant a loan is an unstructured and vagueness task because it is required a tremendous amount of data and many complex relationships among them. Evaluating these many data and relationships is a difficult task even for most experienced decision maker of bank. Therefore, where complex judgement is required, the decision maker of bank may benefit from the use of fuzzy expert network to support the evaluation of ability to pay back. Given the characteristics of decision maker of banking facilities judgement task about ability to pay back, the prototype system named FENET-LG is constructed by integration of fuzzy expert system and neural network. The FENET-LG takes advantage of both the deductive approach of fuzzy expert system and the inductive approach of a neural network to provide a decision aid designed to support and facilitate the process of conducting a judgement of ability to pay back.

• Journal of Communications and Networks
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• v.11 no.2
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• pp.122-133
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• 2009

As wireless spectrum resources become more scarce while some portions of frequency bands suffer from low utilization, the design of cognitive radio (CR) has recently been urged, which allows opportunistic usage of licensed bands for secondary users without interference with primary users. Spectrum sensing is fundamental for a secondary user to find a specific available spectrum hole. Cooperative spectrum sensing is more accurate and more widely used since it obtains helpful reports from nodes in different locations. However, if some nodes are compromised and report false sensing data to the fusion center on purpose, the accuracy of decisions made by the fusion center can be heavily impaired. Weighted sequential probability ratio test (WSPRT), based on a credit evaluation system to restrict damage caused by malicious nodes, was proposed to address such a spectrum sensing data falsification (SSDF) attack at the price of introducing four times more sampling numbers. In this paper, we propose two new schemes, named enhanced weighted sequential probability ratio test (EWSPRT) and enhanced weighted sequential zero/one test (EWSZOT), which are robust against SSDF attack. By incorporating a new weight module and a new test module, both schemes have much less sampling numbers than WSPRT. Simulation results show that when holding comparable error rates, the numbers of EWSPRT and EWSZOT are 40% and 75% lower than WSPRT, respectively. We also provide theoretical analysis models to support the performance improvement estimates of the new schemes.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.3
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• pp.13-23
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• 2020

Currently, online means of replacing resident registration numbers(RRN) include I-Pin, mobile phone, credit card, MyPin, and general-purpose certificate. In order to issue alternative means based on the RRN, it must be designated through the designation review by the Korea Communications Commission(KCC) through a designation review by personal proofing agency and be subject to annual management. However, the criteria for designation and follow-up of the designation of the personal proofing agency carried out by KCC have been used in 2010 without revision, and there are problems that do not conform to the evaluation standards of various alternative means. Therefore, in this paper, we propose a method for improving the designation criteria and management system of the personal proofing service agency. The proposed method analyzes the characteristics of the alternative identification-based personal proofing service and proposes a follow-up management standard that can appropriately evaluate the analyzed characteristics and improves the designation criteria according to the emergence of new alternatives. Through the proposed method, it can be seen that it is possible to strengthen the safety of the personal proofing service based on the alternative means of RRN provided online and face-to-face and to protect the user's personal information.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.259-278
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• 2022

With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.