• Management & Information Systems Review
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• v.39 no.2
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• pp.127-143
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• 2020

As customers' irrational, rude behaviors are often covered by media recently, the issue is becoming a more serious social issue. Workers' stress in the service industry is very severe because they have to face and interact with customers with rude behaviors in-person due to the nature of the job. As a result of customers' rude behaviors, workers even desire to leave their organization because they feel doubts about their job and have negative emotions such as unpleasantness, depression, and fear. Considering that customers' rude behaviors directly impact service industry workers' ability to offer proper service, it is necessary to have appropriate measures against their rude behaviors. This research examined the impact of customers' rude behaviors on service industry workers' emotional dissonance, its impact on job stress, and the impact of job stress on organizational deviance, life violations and creativity. The study also analyzed the moderating effects of stress management education in emotional dissonance and job stress relationship to device ways to manage job stress more positively. To collect data, the study conducted a survey on medical service workers in the customer service sector of large general hospitals and small or medium-sized hospitals in Busan, and the results were as follows. First, rude behaviors had a significant positive(+) effect on emotional dissonance, which had a significant positive(+) effect on job stress. Third, job stress had a significant positive(+) effect on both organizational deviance an life violations. Fourth, job stress had a negative(-) significant effect on creativity. Fifth, there was no moderating effect of stress management education in the relationship between emotional dissonance and job stress.

• Journal of Information Management
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• v.43 no.3
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• pp.61-78
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• 2012

Internet is widely spreading in everyday life and it makes easy to find and share information on the Internet. Many of Internet users are copying and distributing copyrighted materials freely on the Internet without recognizing that it is unethical and illegal behavior. The rate of Internet piracy is constantly increasing even though the regulation and punishment for piracy behavior are to be strict. However, there is a lack of study about the relationship between the punishment and education for intenet piracy on users' attitude and intention toward piracy on the Internet. The purpose of this study is therefore to find out the effect of the level of punishment for internet piracy on users' attitude and intention. This study also examines the moderating effect of piracy education on the relationship between punishment and piracy intention. The study shows that the punishment is directly associated with the attitude but not associated with the piracy intention. The piracy education has a significant effect on the relationship between punishment and intention. The result of this study could bring up the issue of intellectual property protection on the Intenet and suggest an importance of piracy education to educators, managers and internet users.

• Korean Journal of Construction Engineering and Management
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• v.19 no.1
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• pp.21-31
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• 2018

The rapid increase of the elderly living alone is a critical issue in worldwide as it leads to a rapid increase of a social support costs (e.g., medical expenses) for the elderly. In early stages of dementia, the activities of daily living (ADL) including self-care tasks can be affected by abnormal patterns or behaviors and used as an evidence for the early diagnosis. However, extracting activities using non-intrusive approach is still quite challenging and the existing methods are not fully visualized to understand the behavior pattern or routine. To address these issues, this research suggests a model to extract the activities from coarse-grained data (spatio-temporal data log) and visualize the behavioral context information. Our approach shows the process of extracting and visualizing the subject's spaceactivity map presenting the context of each activity (time, room, duration, sequence, frequency). This research contributes to show a possibility of detecting subject's activities and behavioral patterns using coarse-grained data (limited to spatio-temporal information) with little infringement of personal privacy.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.195-200
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• 2019

The role of the Internet of Things in the Fourth Industrial Revolution is in the era of collecting data at the end and analyzing big data through technology to analyze the future or behavior. Therefore, due to the nature of the IoT, it is vulnerable to security and requires a lightweight security protocol. The spread of things Internet technology is changing our lives a lot. IT companies all over the world are already focusing on products and services based on things Internet, and they are going to the era of all things internet that can communicate not only with electronic devices but also with common objects. People, people, people and objects, things and things interact without limitation of time and space, collecting, analyzing and applying information. Life becomes more and more smart, but on the other hand, the possibility of leakage of personal information becomes greater. Therefore, this study proposed security threats that threaten the protection of personal information and countermeasures, and suggested countermeasures for building a secure IoT environment suitable for the Fourth Industrial Revolution.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.6
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• pp.17-32
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• 2003

The information drive of the businesses requires new alternatives in that the promotion of business efficiency through information process technologies ends up conflicting with the protection of information human rights on laborers' side. Nevertheless, apathy on information protection has a tendency to be distorted by the efficiency of the businesses. Should the capital and mass media warn economic red lights, political circles with uneasiness would ignore the significance of information protection on the behalf of business efficiency. Therefore, the importance of information protection is considered a smaller interest than that of business efficiency with the infringements of human rights on laborers' side arising. Informatization of the businesses along with the developments of information process technologies has enabled the management to monitor and control the behaviors of laborers. This new problem needs to establish both information protection mechanism and institutional devices to regulate those labor controls. The security of business activity without human rights infringement warrants both basic rights of the public and spirit of the Constitution. The study suggests the establishment and revision of laws suitable to the period of information human rights. On top of that, the establishment of the basic law for information protection of individuals' with the common principle that integrates the related laws and rules on-off line is needed. This will warrant the active participation of labor unions and create specific alternatives for information protection.

• Informatization Policy
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• v.31 no.2
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• pp.82-104
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• 2024

Smart home services are growing rapidly as the development of the Internet of Things (IoT) opens the era of the so-called "Connected Living." Although personal information leaks through smart home cameras are increasing, however, users-while concerned-tend to take passive measures to protect their personal information. This study theoretically explained and verified how to design effective software update notification messages for smart home cameras to ensure that users comply with the recommended security behavior (i.e., update installation). In a survey experiment participated in by 120 actual users, the effectiveness of both emotional appeals (i.e., security breach warning images for fear appeals) and rational appeals (i.e., loss-framed messages emphasizing the negative consequences of not installing the updates) were confirmed. The results of this study provide theoretical interpretations and practical guidelines on the message design features that are effective for threat appraisals (i.e., severity, vulnerability) of smart home camera users and their protection motivation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.1083-1095
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• 2021

With the recent increase in users' dependence on the Internet and the spread of various IT devices, the influence of information security on the users' has expanded compared to the past. Therefore, it is expected to have an increased influence on information security in personal life. In addition, as the intrusion factors that threaten security continue to become more advanced and diversified (eg., fake news, cyberbullying, identity theft), the need for nurturing information security experts is increasing. Furthermore, not only corporate information security workers, but also all individuals, cannot be free from the threat of information security. Therefore, it is necessary to prepare various information security education to improve information security awareness and induce proactive information security behaviors. In this study, characteristics of domestic and foreign information security education courses are analyzed and provide a standardized framework for information security education applicable to the domestic environment.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2003.12a
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• pp.543-559
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• 2003

The information drive of the businesses requires new alternatives in that the promotion of business efficiency through information process technologies ends up conflicting with the protection of information human rights on laborers’side. Nevertheless, apathy on information protection has a tendency to be distorted by the efficiency of the businesses. Should the capital and mass media warn economic red lights, political circles with uneasiness would ignore the significance of information protection on the behalf of business efficiency. Therefore, the importance of information protection is considered a smaller interest than that of business efficiency with the infringements of human rights on laborers’side arising. Informatization of the businesses along with the developments of information process technologies has enabled the management to monitor and control the behaviors of laborers. This new problem needs to establish both information protection mechanism and institutional devices to regulate those labor controls. The security of business activity without human rights infringement warrants both basic rights of the public and spirit of the Constitution. The study suggests the establishment and revision of laws suitable to the period of information human rights. On top of that, the establishment of the basic law for information protection of individuals’with the common principle that integrates the related laws and rules on-off line is needed. This will warrant the active participation of labor unions and create specific alternatives for information protection.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.