• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.6
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• pp.1305-1317
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• 2019

Although encryption for data protection is essential in the big data platform environment of public institutions and corporations, much performance verification studies on encryption algorithms considering actual big data workloads have not been conducted. In this paper, we analyzed the performance change of AES, ARIA, and 3DES for each of six workloads of big data by adding data and nodes in MongoDB environment. This enables us to identify the optimal block-based cryptographic algorithm for each workload in the big data platform environment, and test the performance of MongoDB by testing various workloads in data and node configurations using the NoSQL Database Benchmark (YCSB). We propose an optimized architecture that takes into account.

• Journal of Convergence for Information Technology
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• v.9 no.2
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• pp.1-6
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• 2019

In this article, we have presented a framework, designed to create new services for businesses, which use large sets of medical data. It is not a simple data analysis step, but it clarifies the purpose of data utilization, analyses it, extracts value from it, and designs a process from actual business or service to an operation. The designed frame work covers the basic architecture and social system model. It was designed, using basic data, which was focused on large sets of medical data, and to be applied to a social system with reference to the designed framework. We are looking forward to create various medical business alliances and services applying the designed framework to the available sets of basic medical data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.666-677
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• 2016

This study analyzes determinants of strategic marketing alliances' performance using 'continuous use intention' of consumers in the Korean credit card industry. Specifically, this study aims to provide comprehensive and synthetic understanding of these factors divided into firm- level and consumer- level variables. Thirty alliance cards were chosen randomly. For firm- level data, managers from the thirty selected cards were interviewed concerning their respective firm and alliance operation. For collection of consumer- level data, 610 card holders from these thirty cards were surveyed concerning card benefits, benefits information, brand image, and continuous use intention. The hierarchical linear model (HLM) was employed to analyze this multi-level data, yielding the following results: First, consumers identified three factors that positively influence continuous use intention. Second, with respect to firmlevel factors, alliance partner's marketing capability is not positively related to intention, whereas fit of alliance goal influences consumer's continuous use of card. Third, contrary to expectation, the positive interaction effects between consumer level variables and firm level variables were found to be not present.

• Journal of the Korea Society for Simulation
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• v.22 no.3
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• pp.55-69
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• 2013

Managers are required to adopt and implement the human resource management practice that fit firm's strategy the most, so that optimize overall performance. However, the time and relative resources that any firm has are limited, which demands managers to understand the relative importance of all sorts of HR practice and promote them in an order of their relative importance. This study follows the universal perspective and contingency perspective(according to firm size and strategy type), try to identify the most effective HR practice on performance as well as their relative importance by "CART Ensemble" analysis. The results are as follows. From universal perspective, firms always need to high level of integration between strategy and HR department, decision making participation, autonomy of speed of working, and autonomy of way of working. Contingency perspective also suggested the importance of integration between HRM and strategy. But others are different case by case. This study suggests useful implications for managers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.111-116
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• 2019

New technologies such as the IoT, Big Data, and Artificial Intelligence, starting from the Web, mobile, and smart device, enable new business models that did not exist before, and various types of Internet companies based on these business models has been emerged. In this research, we examine the factors that influence the success and failure of Internet companies. To do this, we review the recent studies on business model and examine the variables affecting the success of Internet companies in terms of network effect, user interface, cooperation with actors, creating value for users. Using the five derived variables, we will select 14 Internet companies that succeeded and failed in seven commercial business model categories. We derive decision tree by applying inductive learning based on ID3 algorithm to the analysis result and derive rules that affect success and failure based on derived decision tree. With these rules, we want to present the strategic implications for actors to succeed in Internet companies.

• Journal of Digital Convergence
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• v.10 no.8
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• pp.21-28
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• 2012

The study aims to explore industrial and firms' strategic factors affecting diffusion of digital convergence by studying major global IPTV markets. Market and firm variables are selected using the Industrial Organization's SCP approach. Data for the variables are collected from global 31 IPTV operators representing 20 countries. The analysis indicates that the penetration of broadband Internet and the market share of a dominant player in the Pay TV positively affect the penetration of the IPTV service, whereas the penetration of Pay TV, ARPU, firms' strategy and resource do not have influence on its penetration. The study is the cross-country analysis and contributes to the media study by exploring the relationship between market variables and the development of convergent media. Consequently, the study is expected to help policy makers tailor their digital policy for local environment.

• The Journal of the Korea Contents Association
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• v.17 no.3
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• pp.231-237
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• 2017

Threat intelligences collected from cyber incident sharing system and security events collected from Security Information & Event Management system are analyzed and coped with expanding malicious code rapidly with the advent of big data. Analytical classification of the threat intelligence in cyber incidents requires various features of cyber observable. Therefore it is necessary to improve classification accuracy of the similarity by using multi-profile which is classified as the same features of cyber observables. We propose a multi-profile ensemble model performed similarity analysis on cyber incident of threat intelligence based on both attack types and cyber observables that can enhance the accuracy of the classification. We see a potential improvement of the cyber incident analysis system, which enhance the accuracy of the classification. Implementation of our suggested technique in a computer network offers the ability to classify and detect similar cyber incident of those not detected by other mechanisms.

• The Journal of the Korea Contents Association
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• v.19 no.6
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• pp.58-71
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• 2019

The purpose of this study is to explore the multi-dimensionality and the differences of the career success that is revealed by the employee's perception. In order to fulfill the research purpose, LDA topic modeling has applied to extract latent topics of career success from 126 Korean employees' open-end survey questionnaires. The extracted latent topics are social recognition, continuing service within an organization, expertise, financial rewards, and pursuing personal meaning. The occurrence probability of each topic was different by individual characteristics such as gender, education, position. Study findings showed there is multi-dimensionality in career success, and there are differences of topic occurrence probability by demographic characteristics. Additionally, this study showed how to apply the recently developed machine learning approach in order to reduce the researcher's bias by adapting the LDA topic modeling to the qualitative open-ended survey data.

• Journal of the Korea Society of Computer and Information
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• v.5 no.4
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• pp.41-47
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• 2000

In modern dynamic management environment, there is growing recognition that information & knowledge management systems are essential for CEO's efficient/effective decision making. As a key component to cope with this current, we suggest the management performance data-mining system based on IT(Information Technology). This system measures management performance that is considered with both VA(Value-Added), which represents stakeholder's point of view and EVA(Economic Value-Added), which represents shareholder's point of view. The relationship between management performance and 85 financial ratios is analyzed, and then important financial ratios are drawn out. In analyzing the relationship, we applied the explanation-based Gas(Genetic Algorithms) that consider predictability, understanability (lucidity) and reasonability factors simultaneously. To demonstrate the performance of the system, we conducted a case study using financial data over the 16-years from 1981 to 1996 of Korean automobile industry which is taken from database of KISFAS(Korea Investors Services Financial Analysis System).

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.48-63
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• 2019

We tried new analysis including social network analysis(SNA) on the transaction network centered on electronic companies using more than 50 thousand company transaction data obtained from Korean enterprise data (KED) for the year of 2015. We found 97 clusters having more than 10 firms and remarkable 13 clusters having more than 90% sales of the electronic industry in Korea. Clusters are the groups of companies having most of their transactions in the clusters they belong to. We found 5 clusters have 83% of sales in the electronic industry. Most of clusters have main single firms having most of the sales in each clusters except a few clusters. However, we found a few firms to have high rear production linkage effect and found the firms with high linkage effect specially for the small and medium size enterprise (SME). The companies with high production linkage (specially on SMEs) should be managed in terms of (SME) growth policy. The last firm group consisting of the small clusters with less than 10 firms has high employment coefficients. The clusters or company having high production linkage effect on this last firm group should be noted in the terms of employment policy. We also note that there exist the firms with the high value of betweenness coefficients meaning high potential of technology development. They should be managed carefully in terms of technology development policy.