• Korean Security Journal
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• no.21
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• pp.75-94
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• 2009

Since mechanical security systems are mostly composed of electronic, information and communication devices, they have effects in the aspects of overall social environment and crime-oriented environment. Also, the importance is increasing for wireless recognition of RFID and tracing function, which will be usefully utilized in controlling the incomings and outgoings of people/vehicles or allowance, surveillance and control. This is resulting from the increase in the care for the elderly according to the overall social environment, namely, the aging society, and the number of women entering, as well as the increase in the number of heinous crimes. The purpose of this study is to examine the theoretical considerations on ubiquitous sensor network and present a direction for securities companies for their development by focusing on the technological and application areas. To present strategies of response to a new environment for security companies, First, a diversification strategy is needed for security companies. The survival of only high level of security companies in accordance with the principle of liberal market competition will bring forth qualitative growth and competitiveness of security market. Second, active promotion by security companies is needed. It is no exaggeration to say that we are living in the modern society in the sea of advertisements and propaganda. The promotional activities that emphasize the areas of activity or importance of security need to be actively carried out using the mass media to change the aware of people regarding security companies, and they need to come up with a plan to simultaneously carry out the promotional activities that emphasize the public aspect of security by well utilizing the recent trend that the activities of security agents are being used as a topic in movies or TV dramas. Third, technically complementary establishment of ubiquitous sensor network and electronic tag is needed. Since they are used in mobile electronic tag services such as U-Home and U-Health Care, they are used throughout our lives by forming electronic tag environment within safe ubiquitous sensor network based on the existing privacy guideline for the support of mobile electronic tag terminal commercialization, reduction in communication and information usage costs, continuous technical development and strengthening of privacy protection, and the system of cooperation of academic-industrial-research needs to be established among the academic world and private research institutes for these parts.

• Informatization Policy
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• v.23 no.3
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• pp.26-42
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• 2016

Recently, with the rapid growth of the O2O market, Fintech combining the finance and ICT technology is drawing attention as innovation to lead "O2O of finance", along with Fintech-based payment, authentication, security technology and related services. For new technology industries such as Fintech, technical sources, related systems and regulations are important but previous studies on Fintech lack in-depth research about systems and technological trends of the domestic Fintech industry. Therefore, this study aims to analyze domestic Fintech trends and find the insights for the direction of technology and systems of the future domestic Fintech industry by comparing Kakao Pay and Samsung Pay, the two domestic representative mobile payment services. By conducting a complete enumeration survey about the tweets mentioning Fintech until June 2016, this study visualized topics extraction, sensitivity analysis and keyword analyses. According to the analysis results, it was found that various topics have been created in the technologies and systems between 2014 and 2016 and different keywords and reactions were extracted between topics of Samsung Pay based on "devices" such as Galaxy and Kakao Pay based on "service" such as KakaoTalk. This study contributes to analyzing the unstructured data of social media by period by using social media mining and quantifying the expectations and reactions of consumers to services through the sentiment analysis. It is expected to be the foundation of Fintech industry development by presenting a strategic direction to Fintech related practitioners.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• The Journal of Society for e-Business Studies
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• v.20 no.4
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• pp.127-150
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• 2015

Since 9/11 attack, internet has become a major space for terrorist activities and also emerged as the most important spot of lone wolf terrorists for acquiring tools and radicalization. The accident of student Kim's defection to IS (Islamic state) in January 2015 told us that Korea is not any more "terrorism clearance area" and leaded us to look closely into the possibility of lone wolf terrorist. In this paper, I developed a "lone wolf cyber evolution model" using various materials collected by preceding papers and interviewing investigators and terrorism experts in Korea. I analyze Kim's radicalization process using this model. And I picked and closely looked over some facilitating factors of lone wolf such as multi-cultural socialization, increase of international migrants, expansion alienation hierarchy and ideological conflicts deepening and predicted the possibility of lone wolf. Finally, this paper presents some effective policy measurements against lone wolf terrorism in Korea.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.406-412
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• 2022

Storing large amounts of data has always been a big problem from the beginning of computing history. Big Data has made huge advancements in improving business processes by finding the customers' needs using prediction models based on web and social media search. The main purpose of big data stream processing frameworks is to allow programmers to directly query the continuous stream without dealing with the lower-level mechanisms. In other words, programmers write the code to process streams using these runtime libraries (also called Stream Processing Engines). This is achieved by taking large volumes of data and analyzing them using Big Data frameworks. Streaming platforms are an emerging technology that deals with continuous streams of data. There are several streaming platforms of Big Data freely available on the Internet. However, selecting the most appropriate one is not easy for programmers. In this paper, we present a detailed description of two of the state-of-the-art and most popular streaming frameworks: Apache Ignite and Hazelcast. In addition, the performance of these frameworks is compared using selected attributes. Different types of databases are used in common to store the data. To process the data in real-time continuously, data streaming technologies are developed. With the development of today's large-scale distributed applications handling tons of data, these databases are not viable. Consequently, Big Data is introduced to store, process, and analyze data at a fast speed and also to deal with big users and data growth day by day.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.203-209
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• 2023

The paper brings across data that is utilized in the Bring Your Own Device (BYOD) status collected between February and April of 2021 across Saudi Arabia. The data set was collected using questionnaires established through online mechanisms for the respondents. In the questionnaire, personal details included five questions while seven questions addressed the working model of personal mobile devices. Six questions addressed the awareness of employees bring your own device awareness for employees comprised seven questions and two questions addressed the benefits of business achievements. In the identification of suitable respondents for the research, two approaches were applied. The research demanded that the respondents be Saudi Arabian nationals and have attained 18 years. Snowball and purposive techniques were applied in the collection of information from a wide area of Saudi Arabia while employing social media approaches that include the use of WhatsApp and emails in the collection of data. The approach ensured the collection of data from 857 respondents used in the identification of the status as well as issues across the BYOD environment and accompanying solutions. The data was also used in the provision of awareness in the community through short-term courses, cyber security training and awareness programs. The results of the research are therefore applicable to the context of the Saudi Arabian country that is currently facing issues in dealing with the application of personal devices in the work environment.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.286-298
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• 2009

Became large a problem we were productive movement of information became large and occurring to diffusions of development of public media and Internet use. While the Internet became a generalization, public media had more influences and risks, and a crime to abuse anonymity became large in cyber space. In addition, damage is becoming expanded reproduction that infringe of ' crime victim's rights of portrait'. The point that is most important in order to improve these points is recognition regarding the special situation of crime victim, and the ethic consciousness and independent operation regulation and regulation system that these point was taken into consideration in the public media and Internet operation that are an information producer is necessary, and Internet portal shall be included like Internet newspapers to the arbitration object of the Press Arbitration Commission. Also, a legal system regarding personal responsibility shall have for protection of a crime victim's rights of portrait by personal information activity for protection in cyber space. Suggest to a portrait of a crime victim, and an individual and social rights security effort are required for activation regarding an infringement relief system.

• Journal of the Korean Society for Marine Environment & Energy
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• v.20 no.2
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• pp.117-125
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• 2017

SNS Big-data Analysis means to find potential value from big data which has produced by the social media. In this paper, SNS Big-data has been analysed to find Korean concerns by using 24 key words from the marine and fisheries sector. Among 24 key words, seafood, shipping and Dokdo Island are the most mentioned ones. Some key words such as ocean policies and marine security that have less concerns have bess mentioned less. Also, key words that are led by government are mostly mentioned by news media, but key words that are led by private sector and have intimate relationship with people's lives are mostly mentioned by Blogs and Twitters. Therefore, reflecting close national concerns by SNS Big-data Analysis and especially resolving negative factors are the most significant part of the policy establishment. Also, differentiated promotion methods need to be prepared because the frequency of key words mentioned from each type of media are different.

• Journal of Convergence Society for SMB
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• v.5 no.2
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• pp.27-32
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• 2015

Recently, service-related products have gained more attention than general products on the existing social commerce sites. Based on the situation, the effect that the service quality of social commerce has on customer satisfaction was analyzed in this study. It is a study that analyzes how much the service quality affects the customer satisfaction after the purchase, targeting consumers who have made purchases of social commerce products. In the case of social commerce, it is well-known that the diversity and convenience of products have a significant effect on customer satisfaction. Social commerce is currently being dumped beyond the 900 sites and dozens of cases of news, real-time searches of popular portal sites appeared not to be bored enough to related sites to drive the popularity coming quickly dug into our everyday lives of human beings. Yet the perception of social commerce seems not properly established because of the new concept was suddenly going to go through penetration without a collective interpretation and acceptance process. Most of the companies that often mimic the syoseol commerce is large, the blame did not depart from the forms of social shopping. We believe that personal and exhibit their skills and talents, and to wonder to see the social rather than the individuals who make unilateral companies.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.719-728
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• 2016

In this paper, we analyzed IoT patent data using the social network analysis of keyword community network in patents related to Internet of Things technology. To identify the difference of IoT patent trends between Korea and USA, 100 Korea patents and 100 USA patents were collected, respectively. First, we first extracted important keywords from IoT patent abstracts using the TF-IDF weight and their correlation and then constructed the keyword network based on the selected keywords. Second, we constructed a keyword community network based on the keyword community and performed social network analysis. Our experimental results showed while Korea patents focus on the core technologies of IoT (such as security, semiconductors and image process areas), USA patents focus on the applications of IoT (such as the smart home, interactive media and telecommunications).