• Convergence Security Journal
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• v.4 no.3
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• pp.1-8
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• 2004

Large distributed systems such as computational and data grids require that a substantial amount of monitoring data be collected for various tasks such as fault detection, performance analysis, performance tuning, performance prediction, security analysis and scheduling. to cope with this problem, they are needed network monitoring architecture which can collect various network characteristic and analyze network security state. In this paper, we suggest network performance and security analysis system based on network monitoring. The System suggest that users can see distance network state with tuning network parameters.

• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.92-98
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• 2008

Network data modeling is a essential research for the evaluation for intrusion detection systems performance, network modeling and methods for analyzing network data. In network data modeling, real data from the network must be analyzed and the modeled data must be efficiently composed to reflect a sufficient amount of the original data. In this parer the useful elements of real network data were quantified from packets captured from a huge network. Futhermore, a statistical analysis method was used to find the most effective element for efficiently classifying the modeled data.

• Journal of Information Management
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• v.36 no.4
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• pp.199-215
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• 2005

Experts participating in the knowledge expert network externalize their implicit knowledge by providing information or writing reports. Almost all the members of the network share externalized knowledge and the network facilitate the dissemination and diffusion of knowledge. Individuals reproduce another implicit knowledge by internalizing shared knowledge through the network and re-created knowledge is externalized, establishing knowledge circulation. In this paper, we analyze the expert groups of the Global Network of Korean Scientists & Engineers(KOSEN, www.kosen21.org), the Korea's No. 1 science and engineering knowledge expert community, with the application of the theory of policy network proposed by Marsh & Rhodes. According to the principal standards of policy network classification such as the number of participants, interaction among participants, consistency, distribution of resources and dependency, we categorize the KOSEN expert groups as closed policy network and opened issue network, and divide closed policy network into core community and periphery community.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.48-59
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• 2018

Recently, network technology has been used in various fields due to development of network technology. However, there has been an increase in the number of attacks targeting public institutions and companies by exploiting the evolving network technology. Meanwhile, the existing network intrusion detection system takes much time to process logs as the amount of network log increases. Therefore, in this paper, we propose a Spark-based network log analysis system that detects unstructured network attack pattern. by using Snort. The proposed system extracts and analyzes the elements required for network attack pattern detection from large amount of network log data. For the analysis, we propose a rule to detect network attack patterns for Port Scanning, Host Scanning, DDoS, and worm activity, and can detect real attack pattern well by applying it to real log data. Finally, we show from our performance evaluation that the proposed Spark-based log analysis system is more than two times better on log data processing performance than the Hadoop-based system.

• Korean Journal of Construction Engineering and Management
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• v.7 no.2 s.30
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• pp.162-170
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• 2006

Neural network analysis is expected to enhance the forecasting ability for the real estate market. This paper reviews definition, structure, strengths and weaknesses of neural network analysis, and verifies the applicability of neural network analysis for the real estate market. Neural network analysis is compared with regression analysis using the same sample data. The analyses model the macroeconomic parameters that influence the sales price of apartments. The results show that neural network analysis provides better forecasting accuracy than regression analysis does, what confirms the applicability of neural network analysis for the real estate market.

• KSBB Journal
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• v.24 no.3
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• pp.287-290
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• 2009

Metabolic network is composed of more than thousands of metabolic reactions. Therefore, understanding of metabolic behavior of microorganisms is required to engineer metabolism of microorganisms. In this paper, we employed ARACNE (Algorithm for the Reconstruction of Accurate Cellular Networks) to quantify relationships among metabolic subpathways. The results showed that ARACNE analysis can give new insight into the study of bacterial metabolism.

• The Journal of the Korea Contents Association
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• v.13 no.7
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• pp.16-23
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• 2013

This paper analyzes the artistic practical use of social network visualization through the aesthetic information interpretation. The first social network visualization has emerged as 'Sociogram' in the form of social network analysis(SNA). Since social network has complex, the analyzing technology of social network has emerged. Early social network visualization has a practical purpose to measure the social structure, but current social network visualization divided into various forms from artistic expressions through information. This paper divide into two categories based on the artistic application of social network visualization. First, this research focuses on the static graph based on analog. Second, this research analyze the category of interacted visualization to generate a real-time digital image. This paper presents the fusion of paradigm between engineering and art through this way.

• Journal of the Korean association of regional geographers
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• v.12 no.6
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• pp.693-703
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• 2006

Keeping the balance between exploration of new possibilities and exploitation of existing certainties in organizational innovation is getting its significance as business environments become more turbulent This paper focused on the relationship between two different types of innovation and network configuration. For this purpose, we conducted the empirical studies of 168 IT SMEs located in Gyeongbuk. For this analysis, we defined two innovation types as exploratory innovation and exploitative innovation. Also, we considered network scope and strength of tie as network configuration. The results showed that the exploratory innovation had sparse network of network scope and weak tie of strength. On the contrary the exploitative innovation had dense network and strong tie.

• Information Systems Review
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• v.17 no.2
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• pp.179-192
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• 2015

Collaborative research has been actively done on the basis of academic relationships among various study area. The importance of collaboration has also been increased. Collaborative researchers can reduce time, cost, and research risk to maximize research productivity. This study aims to develop a framework for understanding the behavior of professional groups through network characteristics. To achieve the goal, we collected data of the co-authored network and that of the reviewer network from from 2006 to 2012. Total 230 submitted papers were analyzed on the views of research performance and productivity. Various analytical methods such as centrality analysis, sub-group analysis, correlation, and regression were conducted for assuring the reliability and validity of our research. The results shows that the productivity of the co-authored network was increased and the efficiency of the reviewer network was also identified through several network indexes.

• The Journal of the Korea Contents Association
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• v.16 no.6
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• pp.671-679
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• 2016

We investigated subgroups within a global communication network to improve the empirical understanding of global communication phenomenon from the social network perspective. We collected global communication data from Twitter and constructed a global communication network. We also added countries' geographic and economic properties used in the United Nations and the World Economic Forum. We analyzed the subgroups' structure within the global communication network using centrality analysis, core-peripheral analysis, and cohesion analysis. We also detected communities embedded within the global communication network with modularity-based community detection methods. We found that the core countries occupy central positions in the global communication network and there is a hierarchical communication structure among the economic subgroups. Futhermore, we discovered some communities within the global communication network and found that countries within the communities can have homophily such as economy, geography, history, culture, and religion.