• Journal of the Korea society of information convergence
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• v.5 no.2
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• pp.67-76
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• 2012

XML-based open protocol, XMPP users to pass messages to other users, which means that a decentralized communication network is the network infrastructure and enable it. In addition, XMPP servers using a professional server-to-server protocol to communicate with each other and decentralized social networks and collaboration framework provides an important possibility. In this paper, the features of XMPP messaging protocol is applicable to automotive telematics terminals XMPP-based platform design, and presence of two-way communication point for the problem, point-to-point session setup issues, security issues, compatibility issues, and to solve the scalability problem XMPP-based messaging system was implemented.

• Journal of Information Technology Services
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• v.20 no.4
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• pp.1-21
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• 2021

At a time when the e-commerce market is experiencing accelerated growth, with advancements in information and communications technology (ICT), the problems of distribution of counterfeit products and consumer confusion caused by non-face-to-face purchases have increased. Hence, amid intensifying competition, it has become important for e-commerce companies deliver product information more efficiently, provide differentiated services, and secure credibility for consumers by reducing consumer damage from buying counterfeit products. However, even though consumer confusion and the inadvertent purchase of counterfeit products are intensifying in such a market scenario, there are no services that aim to solve such problems. This study examines the conventional e-commerce industry in South Korea through a political, economic, social, and technological (PEST) analysis, based on in-depth interviews with consumers, to derive the pain and gain points of the industry. As a result, the inherent problems of the e-commerce industry were revealed. Through a service value network perspective, services aimed at resolving such issues were derived, and the e-commerce business ecosystem needed to solve this problem was deduced. The findings revealed that the artificial intelligence-based service support platform has become a major driving force within the e-commerce innovation ecosystem by enabling a new way to create and secure value using ICT. This entails a new exchange mechanism and transaction architecture and a new organizational structure that breaks the barriers between industries.

• The Journal of Information Systems
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• v.28 no.1
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• pp.73-96
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• 2019

Purpose The purpose of this study is to examine the effect of communication-structure characteristics on performance in online collaboration using the data from Github, one of representative open source software development platforms. We analyze the impact of in-degree/out-degree centralization and reciprocity of communication network on collaboration performance in each project. In addition, we investigate the moderating effect of owner types, an individual developer or an organization. Design/methodology/approach We collect the data of 838 Github projects, and conduct social network analysis for measuring in-degree/out-degree centralization and reciprocity as independent variables. With these variables, hierarchical regression analysis is employed on the relationship between the characteristics of communication structure and collaborative performance. Findings Our results show that for the project owned by an organization, the centralized structure of communication is not associated with the collaboration performance. In addition, the reciprocity is positively related to the collaboration performance. On the other hand, for the project owned by an individual developer, the centralized structure of communication is positively related to the performance, and the reciprocity does not show the positive relationship on the performance.

• The Journal of Society for e-Business Studies
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• v.21 no.2
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• pp.23-46
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• 2016

With the increasing socio-economic value of an open collaboration over the Internet, it has become significantly important to successfully manage open source software development program. Most of the previous research have focused on various factors that influence the performance of the project, but studies on how the project owners recognized as "leader" affect the outcome of the project are very limited. This research investigates how individual and governance characteristics of an owner influences the performance of project based on impression formation and social capital theory. For a data set, we collect 611 Repositories and the owner's data from the open source development platform Github, and we form knowledge sharing network of an each repository by using social network analysis. We use hierarchical regression analysis, and our results show that a leader, who exposes a lot of one's personal information or who has actively followed and showed interests to communicate with other developers, affects positive impacts on project performance. A leader who has a high centrality in knowledge sharing network also positively affects on project performance. On the other hand, if a leader was highly willing to accept external knowledge or is recognized as an expert in the community with large numbers of followers, the result show negative impacts on project performance. The research may serve as a useful guideline not only for the future open source software projects but also for the effective management of different types of open collaboration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.5062-5079
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• 2017

Malicious insider threats have increased recently, and methods of the threats are diversifying every day. These insider threats are becoming a significant problem in corporations and governments today. From a technology standpoint, detecting potential insider threats is difficult in early stage because it is unpredictable. In order to prevent insider threats in early stage, it is necessary to collect all of insiders' data which flow in network systems, and then analyze whether the data are potential threat or not. However, analyzing all of data makes us spend too much time and cost. In addition, we need a large repository in order to collect and manage these data. To resolve this problem, we develop an indicator-based behavior ontology (IB2O) that allows us to understand and interpret insiders' data packets, and then to detect potential threats in early stage in network systems including social networks and company networks. To show feasibility of the behavior ontology, we developed a prototype platform called Insider Threat Detecting Extractor (ITDE) for detecting potential insider threats in early stage based on the behavior ontology. Finally, we showed how the behavior ontology would help detect potential inside threats in network system. We expect that the behavior ontology will be able to contribute to detecting malicious insider threats in early stage.

• Journal of Ocean Engineering and Technology
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• v.36 no.5
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• pp.313-325
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• 2022

Recently around the world, coastal erosion is paying attention as a social issue. Various constructions using low-crested and submerged structures are being performed to deal with the problems. In addition, a prediction study was researched using machine learning techniques to determine the wave attenuation characteristics of low crested structure to develop prediction matrix for wave attenuation coefficient prediction matrix consisting of weights and biases for ease access of engineers. In this study, a deep neural network model was constructed to predict the wave height transmission rate of low crested structures using Tensor flow, an open source platform. The neural network model shows a reliable prediction performance and is expected to be applied to a wide range of practical application in the field of coastal engineering. As a result of predicting the wave height transmission coefficient of the low crested structure depends on various input variable combinations, the combination of 5 condition showed relatively high accuracy with a small number of input variables defined as 0.961. In terms of the time cost of the model, it is considered that the method using the combination 5 conditions can be a good alternative. As a result of predicting the wave transmission rate of the trained deep neural network model, MSE was 1.3×10^-3, I was 0.995, SI was 0.078, and I was 0.979, which have very good prediction accuracy. It is judged that the proposed model can be used as a design tool by engineers and scientists to predict the wave transmission coefficient behind the low crested structure.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.5
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• pp.37-48
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• 2022

With development of Digital Technology, social issues are communicated through digital-based platform such as SNS and form public opinion. This study attempted to analyze big data from Twitter, a world-renowned social network service, and find out the public opinion. After collecting Twitter data based on 14 keywords for 1 year in 2021, analyzed the term-frequency and relationship among keyword documents with pearson correlation coefficient using Data-mining Technology. Furthermore, the 6 main topics that on the center of information security field in 2021 were derived through topic modeling using the LDA(Latent Dirichlet Allocation) technique. These results are expected to be used as basic data especially finding key agenda when establishing strategies for the next step related industries or establishing government policies.

• Management & Information Systems Review
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• v.29 no.4
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• pp.143-167
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• 2010

Diverse research topics relating to Social Network Services (SNS) such as, social affective factors in relationships among internet users, social capital value of SNS, comparing attributes why users are intending to participate in SNS, user's lifestyle and their preferences, and the exploratory seeking potential of SNS as a social capital need to be focused on. However, these researches that have been undertaken only consider facts at a particular period of the changing computing environment. In accordance with this indispensability, the integrated view on what technical, social and business characteristics and attributes need to be acknowledged. The purpose of this study is to analyze the evolving attributes and characteristics of SNS from Web 1.0 to Mobile web 2.0 through the Web 2.0 and Mobile 1.0 period. Based on the relevant literature, the attributes that drive the changing technological, social and business aspects of SNS have been developed and analyzed. This exploratory study analyzed major attributes and relationships between SNS and users by changing the paradigms which represented each period. It classified and chronicled each period by representing paradigms and deducted the attributes by considering three aspects such as technological, social and business administration. The major findings of this study are, firstly, the web based computing environment has been changed into the platform attribute for users in the aspect of technology. Users can only read, listen and view information through the web site in the early stages, but now it is possible that users can create, modify and distribute all kinds of information. Secondly, the few knowledge producers of web services have been changed into a collective intelligence by groups of people in the aspect of society. Information authority has been distributed and there is no limit to its spread. Many businesses recognized the potential of the SNS and they are considering how to utilize these advantages toward channel of promotion and marketing. Thirdly, the conventional marketing channel has been changed into oral transmission by using SNS. The market of innovative mobile technology such as smart phones, which provide convenience and access-ability toward customers, has been enlarged. New opportunities to build friendly relationship between business and customers as a new marketing chance have been created. Finally, the role of the consumer has been changed into the leading role of a prosumer. Users can create, modify and distribute information, and are performing the dual role of customer and producer.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.8
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• pp.1551-1559
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• 2015

Recently, the performance of smart devices is almost similar to that of the existing PCs, thus the users of smart devices can perform similar works such as messengers, SNSs(Social Network Services), smart banking, etc. originally performed in PC environment using smart devices. Although the development of smart devices has led to positive impacts, it has caused negative changes such as an increase in security threat aimed at mobile environment. Specifically, the threats of mobile devices, such as leaking private information, generating unfair billing and performing DDoS(Distributed Denial of Service) attacks has continuously increased. Over 80% of the mobile devices use android platform, thus, the number of damage caused by mobile malware in android platform is also increasing. In this paper, we propose android based malware detection mechanism using time-series analysis, which is one of statistical-based detection methods.We use auto-regressive moving-average model which is extracting accurate predictive values based on existing data among time-series model. We also use fast and exact malware detection method by extracting possible malware data through Z-Score. We validate the proposed methods through the experiment results.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.71-86
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• 2023

The purpose of this exploratory study is to compare the differences in public perceptual characteristics of Korean and Chinese societies regarding the metaverse using big data analysis. Due to the environmental impact of the COVID-19 pandemic, technological progress, and the expansion of new consumer bases such as generation Z and Alpha, the world's interest in the metaverse is drawing attention, and related academic studies have been also in full swing from 2021. In particular, Korea and China have emerged as major leading countries in the metaverse industry. It is a timely research question to discover the difference in social awareness using big data accumulated in both countries at a time when the amount of mentions on the metaverse has skyrocketed. The analysis technique identifies the importance of key words by analyzing word frequency, N-gram, and TF-IDF of clean data through text mining analysis, and analyzes the density and centrality of semantic networks to determine the strength of connection between words and their semantic relevance. Python 3.9 Anaconda data science platform 3 and Textom 6 versions were used, and UCINET 6.759 analysis and visualization were performed for semantic network analysis and structural CONCOR analysis. As a result, four blocks, each of which are similar word groups, were driven. These blocks represent different perspectives that reflect the types of social perceptions of the metaverse in both countries. Studies on the metaverse are increasing, but studies on comparative research approaches between countries from a cross-cultural aspect have not yet been conducted. At this point, as a preceding study, this study will be able to provide theoretical grounds and meaningful insights to future studies.