• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.728-739
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• 2020

Using webometric big data, this study examines the diversity of online information sources about the novel coronavirus causing the COVID-19 pandemic. Specifically, it focuses on some 28 countries where confirmed coronavirus cases occurred in February 2020. In the results, the online visibility of Australia, Canada, and Italy was the highest, based on their producing the most relevant information. There was a statistically significant correlation between the hit counts per country and the frequency of visiting the domains that act as information channels. Interestingly, Japan, China, and Singapore, which had a large number of confirmed cases at that time, were providing web data related to the novel coronavirus. Online sources were classified using an N-tuple helix model. The results showed that government agencies were the largest supplier of coronavirus information in cyberspace. Furthermore, the two-mode network technique revealed that media companies, university hospitals, and public healthcare centers had taken a positive attitude towards online circulation of coronavirus research and epidemic prevention information. However, semantic network analysis showed that health, school, home, and public had high centrality values. This means that people were concerned not only about personal prevention rules caused by the coronavirus outbreak, but also about response plans caused by life inconveniences and operational obstacles.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.157-163
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• 2021

This study attempted to find individual reasons for inducing cybercrime. The survey was conducted targeting investigators and security experts on 11 types of cybercrime. There are 16 internal factors that cause crime and classified according to Maslow's 5 steps. As a result of the survey on a total of 176 items, the credibility of the Cronbach's Alpha coefficient was 0.925. The result of the factor analysis is as follows. Factor analysis results are maslow phase 1 physiological desire is commercial, sykes. Phase 2 safety desires are not punishable and crowd. The three-stage social desire is impulsiveness, indifference, etc. The fourth stage of respect is anonymity and honor. The desire for self-reality in stage 5 has been reduced to indesity, a loss of moderation, morality, and media effects. In conclusion, the physiological desire, the desire for respect for the crime of infringing on the information and communication network, the desire for menstruation, the desire for self-realization for the crime of using information and communication networks, the desire for self-actualization for the crime of illegal content. It was in the order of desire.

• The Journal of Korean Association of Computer Education
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• v.14 no.6
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• pp.1-10
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• 2011

Since IT technology grow rapidly, our ethic of consciousness has become big issue with adverse effect. Many scholar has discussed and tired to solve this problem, but it is still helpless to fix. Therefor in this paper, author will not suggest the solution, but will present model list of adverse effects and cases to prevent accidents. The model list of adverse effects, what author will present is about media addiction, harmful content, cyber-violence, right infringement, cyber terror and decision obstacle. This model list is made by primary and secondary survey. This model will show adverse effect of present day, but also will show future adverse effects that can be prevent. Through out this paper, this model list could use for education plan.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.6 s.336
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• pp.53-60
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• 2005

Considerable efforts has been recently devoted to the determination of accurate channel models for the power line environment, both for the indoor and outdoor cases. The common limitation of the known and previously published models is the particular type of approach followed. This paper is concerned with a power line channel characteristic measurement for the more fast and efficiently power line communication experiment. The need arises from the fact that indoor power cables consist of conductors and inductors. A capacitive load simulator is a essential equipment in the power line modem development for indoor power line network. We accomplished a channel data base by the frequency response method about the total 224 capacitor load cases. On the basis of this measurement modeling it is here revealed that the power line communication channel is a more deterministic media.

• Journal of the Korea Society of Computer and Information
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• v.26 no.8
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• pp.229-237
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• 2021

This paper aims to study the using motivation and influencing factors of Chinese users' participation in live stream shopping through theoretical and empirical analysis, so as to evaluate the change in users' needs and improve marketing strategies. In doing so, I conducted a questionnaire survey for Chinese live stream shopping users and collected the required data. For empirical analysis, I used SPSS and AMOS software to carry out descriptive analysis, reliability and validity analysis and structural equation model analysis (SEM) to test the hypothesis. The results of the analysis showed that core competency and brand personality of the short video industry have a significant impact on user and customer perceived value, thus influencing users' using motivation. That is, users do not blindly follow live stream shopping but make their active choice. Therefore, it is suggested that live stream shopping platform should strengthen the e-commerce attributes and eradicate "the sense of false satisfaction", in order to achieve the effective communication of information. On the other hand, to stimulate the purchase motivation of users, the brand should build up its personality, and enhance user and customer perceived value in cyber marketing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1137-1143
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• 2015

Sensitive internal information has been transmitted in a variety of services of Internet environment, but almost users do not know what internal information is sent. In this paper, we intend to develop a new filtering system that continuously monitors the sensitive information in outbound network packets and notifies the internal user whether or not to expose. So we design a filtering system for sensitive information and analyze the implementation results. Thus users visually can check whether disclosure of the important information and drop the corresponding packets by the proposed system. The results of this study can help decrease cyber threats various targeting internal information of company by contributing to prevent exposure of sensitive internal information.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.125-134
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• 2014

As the social media which was simple communication media is activated on account of twitter and facebook, it's usability and importance are growing recently. Although many companies are making full use of its the capacity of information diffusion for marketing, the adverse effects of this capacity are growing. Because social network is formed and communicates based on friendships and relationships, the spreading speed of the spam and mal-ware is very swift. In this paper, we draw parameters affecting malicious data diffusion in social network environment, and compare and analyze the diffusion capacity of each parameters by propagation experiment with XSS Worm and Koobface Worm. In addition, we discuss the structural characteristics of social network environment and then proposed malicious data propagation model based on parameters affecting information diffusion. n this paper, we made up BA and HK models based on SI model, dynamic model, to conduct the experiments, and as a result of the experiments it was proved that parameters which effect on propagation of XSS Worm and Koobface Worm are clustering coefficient and closeness centrality.

• Smart Media Journal
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• v.9 no.3
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• pp.71-79
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• 2020

Mobile network is used by many users worldwide for diverse services, including phone-call, messaging and data transfer over the Internet. However, this network may experience massive damage if it is exposed to cyber-attacks or denial-of-service attacks via wireless communication interference. Because the mobile network is also used as an emergency network in cases of disaster, evaluation or verification for security and safety is necessary as an important nation-wide asset. However, it is not easy to analyze the mobile core network because it's built and serviced by private service providers, exclusively operated, and there is even no separate network for testing. Thus, in this paper, a virtual mobile network is built using OpenAirInterface, which is implemented based on 3GPP standards and provided as an open source software, and the structure and protocols of the core network are analyzed. In particular, the S1AP protocol messages captured on S1-MME, the interface between the base station eNodeB and the mobility manager MME, are analyzed to identify potential security threats by evaluating the effect of the messages sent from the user terminal UE to the mobile core network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1224-1230
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• 2020

Since the spread of smart phones, interest in wearable devices has increased and diversified, and is closely related to the lives of users, and has been used as a method for providing personalized services. In this paper, we propose a method to detect the user's behavior by applying information from a 3-axis acceleration sensor and a 3-axis gyro sensor embedded in a smartphone to a convolutional neural network. Human behavior differs according to the size and range of motion, starting and ending time, including the duration of the signal data constituting the motion. Therefore, there is a performance problem for accuracy when applied to a convolutional neural network as it is. Therefore, we proposed a Time-Division Feature Fusion Convolutional Neural Network (TDFFCNN) that learns the characteristics of the sensor data segmented over time. The proposed method outperformed other classifiers such as SVM, IBk, convolutional neural network, and long-term memory circulatory neural network.

• Korean journal of communication and information
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• v.40
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• pp.45-79
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• 2007

This study explored three questions: (1) what are the motives of producing and using user-created contents (UCC, video clips which are produced and uploaded at various web sites by individuals), (2) what are the gratifications that users obtain from UCC, and (3) what are the differences of gratifications according to individual uses of UCC. A survey was conducted to 258 UCC users and data were factor-analyzed to find the dimensions of motives and gratifications. As for the motives of UCC uses, six factors were constructed: self-expression, private life, participation, information retrieval, rest, and entertainment, among which self-expression showed the largest variation. As for the gratifications, five factors were constructed: self-expression, rest, information retrieval, socializing, and entertainment.