• KIPS Transactions on Computer and Communication Systems
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• v.2 no.12
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• pp.533-540
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• 2013

Anonymity is the one of main reasons for substantial improvement of Internet. It encourages various users to express their opinion freely and helps Internet based distributed systems vitalize. But, anonymity can cause unexpected threats because personal information of an online user is hidden. Especially, distributed systems are threatened by Sybil attack, where one malicious user creates and manages multiple fake online identities. To prevent Sybil attack, the traditional solutions include increasing the complexity of identity generation and mapping online identities to real-world identities. But, even though the high complexity of identity generation increases the generation cost of Sybil identities, eventually they are generated and there is no further way to suppress their activity. Also, the mapping between online identities and real identities may cause high possibility of losing anonymity. Recently, some methods using online social network to prevent Sybil attack are researched. In this paper, a new method is proposed for extracting a user's system-wide Sybil-resistant trust value by using the properties embedded in online social network graphs. The proposed method can be categorized into 3 types based on sampling and decision strategies. By using graphs sampled from Facebook, the performance of the 3 types of the proposed method is evaluated. Moreover, the impact of Sybil attack on nodes with different characteristics is evaluated in order to understand the behavior of Sybil attack.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.35-51
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• 2019

The two main goals of this study are to derive independent factors affecting the success rate of crowdfunding and to empirically analyze the variation of independent factors' effects on the success of crowdfunding by industry (Internet, culture/art, manufacturing/distribution), and funding type (stock type, bond type). To identify the success factors of crowdfunding for invigoration and strategic utilization, first, several variables were refined after interviews with experts and platform operators with investment experiences in numerous crowdfunding projects. Then, independent factors affecting project involvement were categorized as follows: a characteristic of project, participant activity, and enterprise. Also, the results derived from the influence of independent variables on crowdfunding after moderating effects were driven. Selected independent factors in this study are as follows: crowdfunding period, target amount, visual contents, minimum account money, number of comments, number of SNS followers, level of interest, financial Statement disclosure, investment attraction, venture company, intellectual property rights disclosure, and business operation period. Selected moderating factors in this study are as follows: industry (Internet, culture/art, manufacturing/distribution), and funding type (stock type, bond type). In conclusion, a discussion of the academical and practical implications and a suggestion of directions for further research are explained.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.265-277
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• 2019

The purpose of this study was to compare the effects of elastic band exercises and lunge on the knee Electromyography and Q-Angle in people with genu varum. The subjects of this study were healthy general people who had genu varum of 18 subjects. The subjects were randomly divided into two groups as a elastic band group (n=9, 6 males and 3 females, age: $22.55{\pm}2.05years$, height: $169.8{\pm}6.07cm$, weight: $66.44{\pm}9.83kg$) and a lunge group (n=9, 7 males and 2 females, age: $23.88{\pm}1.37years$, height: $173.66{\pm}6.72cm$, weight: $67.22{\pm}13.30kg$).The elastic band exercise and the lunge were performed every week, for four weeks. These results suggest that the Q-Angle of both knees showed differences before and after the intervention in elastic band group and lunge group. Also, The MVIC was no changes in both groups before and after the intervention except for the left foot in elastic band group and lunge group. As a result, the space distance of knees in both groups was significantly reduced. These result suggested that the elastic band exercise and lunge were effective ways in alleviating genu varum.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.295-304
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• 2019

This paper introduces a customized Smart Fire and Crime system for one person households. Recently, the number of one person household has skyrocketed due to the increasing number of one person household and the aging population. As a result, the demand for private security companies for one person household is increasing and smart security systems that are applied with rapidly evolving IoT and sensor technologies are also becoming a major issue. However, despite the increasing trend of one person households, the existing system focuses on multiple households, so that there are disadvantages of the one person households to operate in such a big system which operate separately. Therefore, in this paper, we design and implement a system that provides a personalized safety service for one person household that integrates a security system and a fire monitoring system. This will help prevent criminal activity in places where the police can not reach at a lower cost than using existing private companies, and help monitor the situation of the houses in real time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.79-86
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• 2021

In order to increase the probability of success in big data projects, quantified techniques are required to analyze the root cause of risks from complex causes and establish optimal countermeasures. To this end, this study measures risk factors and relationships through SNA analysis and presents a way to respond to risks based on them. In other words, it derives a dependency network matrix by utilizing the results of correlation analysis between risk groups in the big data projects presented in the preliminary study and performs SNA analysis. In order to derive the dependency network matrix, partial correlation is obtained from the correlation between the risk nodes, and activity dependencies are derived by node by calculating the correlation influence and correlation dependency, thereby producing the causal relationship between the risk nodes and the degree of influence between all nodes in correlation. Recognizing the root cause of risks from networks between risk factors derived through SNA between risk factors enables more optimized and efficient risk management. This study is the first to apply SNA analysis techniques in relation to risk management response, and the results of this study are significant in that it not only optimizes the sequence of risk management for major risks in relation to risk management in IT projects but also presents a new risk analysis technique for risk control.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.515-520
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• 2022

In context awareness using multiple sensors, when using sensor data detected and sent by each sensor, it is necessary to give different weights for each sensor. Even if the same type of sensor is configured for the same situation, sometimes it is necessary to assign different weights due to other secondary factors. It is inevitable to assign weights to events in the real world, and it can be said that a weighting method that can be used in a context awareness system using multiple sensors is necessary. In this study, we propose a weighting method for each sensor that reports to the host while the sensors continue to detect over time. In most IoT environments, the sensor continues the detection activity, and when the detected value shows a change pattern beyond a predetermined range, it is basically reported to the host. This can be called a kind of data stream environment. A weighting method was proposed for sensing data from multiple sensors in a data stream environment, and the new weighting method was to select and assign weights to data that indicates a context change in the stream.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.155-163
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• 2022

In order to avoid the spread of Covid-19, outdoor activities are decreasing worldwide and the time spent at home is increasing. As physical activity declines, the number of people who feel bored, restless and immune deficient is increasing. As indoor life becomes more permanent, multiple approaches to home workout are becoming active. This paper examines how the Covid blue (boredom and social anxiety) produced in the no-touch era affects quality of life through the use of home training applications. Questionnaires were collected from Chinese people using a website dedicated to Chinese questionnaires, and finally 383 appropriate data were analyzed using SPSS24.0 and AMOS24.0. The research results showed that the actual experience of using home workout had a positive impact on quality of life. The higher the user's sense of social unease about being late in the untact, It was found that the higher the social anxiety perceived by users about the untact era, the higher the interactivity and exercise satisfaction with the home workout app. Home workout application can improve exercise satisfaction and quality of life, which are more positive effects beyond the result of resolving consumers' boredom. Therefore, it can be used as a channel for digital services.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.31-38
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• 2022

An electrocardiogram(ECG) is a recoding of electrical signals of the heart's cyclic activity and an important body information for diagnosing myocardial rhythm. Large amount of information are generated continuously and a significant period of cumulative signal is required for the purpose of diagnosing a specific disease. Therefore, research on compression including clinically acceptable lossy technique has been developed to reduce the amount of information significantly. Recently, wearable smart heart monitoring devices that can transmit electrocardiogram(ECG) are being developed. The use of electrocardiogram, an important personal information for healthcare service, is rapidly increasing. However, devices generally have limited capability and power consumption for user convenience, and it is often difficult to apply the existing compression method directly. It is essential to develop techniques that can process and transmit a large volume of signals in limited resources. A method for compressing and transmitting the ECG signals efficiently by using the cumulative average (template) of the unit waveform is proposed in the paper. The ECG is coded lovelessly using template matching. It is analyzed that the proposed method is superior to the existing compression methods at high compression ratio, and its complexity is not relatively high. And it is also possible to apply compression methods to template matching values.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.39-48
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• 2022

Cyberattacks around the world continue to increase, and their damage extends beyond government facilities and affects civilians. These issues emphasized the importance of developing a system that can identify and detect cyber anomalies early. As above, in order to effectively identify cyber anomalies, several studies have been conducted to learn BGP (Border Gateway Protocol) data through a machine learning model and identify them as anomalies. However, BGP data is unbalanced data in which abnormal data is less than normal data. This causes the model to have a learning biased result, reducing the reliability of the result. In addition, there is a limit in that security personnel cannot recognize the cyber situation as a typical result of machine learning in an actual cyber situation. Therefore, in this paper, we investigate BGP (Border Gateway Protocol) that keeps network records around the world and solve the problem of unbalanced data by using SMOTE. After that, assuming a cyber range situation, an autoencoder classifies cyber anomalies and visualizes the classified data. By learning the pattern of normal data, the performance of classifying abnormal data with 92.4% accuracy was derived, and the auxiliary index also showed 90% performance, ensuring reliability of the results. In addition, it is expected to be able to effectively defend against cyber attacks because it is possible to effectively recognize the situation by visualizing the congested cyber space.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.153-161
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• 2022

The current National Curriculum clearly states that students should utilize digital information as a core competency. With ICT-based non-face-to-face learning has become commonplace, that ability has become as basic and essential as the competency to read and write in traditional education. Therefore, this work analyzed the characteristics of ICT utilization learning in the social studies curriculum of elementary school to cultivate basic abilities and skills for learners' future, and these discussed from the perspective of digital literacy. The results are as follows. First, the ICT utilization learning could be found in most units for the subject, but most of them were just the searching material and the watching video. Second, when approached from the perspective of digital literacy, the main activities were the 'access' in the lowest level. Third, the higher levels such as 'understand' and 'create' were few activities. This result gave the task of reflecting on the ICT education so far. Rather than just focusing on increasing the frequency of the ICT using, it is necessary to improve the quality of students' activities in ICT learning for progressing digital literacy. For the students' skills of utilizing digital information could be developed differently depending on the type of ICT learning activity.