• Information Systems Review
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• v.17 no.3
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• pp.77-94
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• 2015

As Internet has become a popular media for sharing information, users create and share tremendous volume of information including large amount of personal information in cyberspace. Sharing private information online can enhance strength of social relationship but it could also bring negative consequences like information privacy invasion. Although many companies and governments address the importance of information privacy online, there are countless cases of crimes and hackings relating personal information online world wide. Since there are some researches investigating the role of governments and organizations on online privacy domain but there is little research regarding users' privacy protection behaviors. This study investigates relationship between Internet users' information privacy protection behavior and environmental factors. Especially, this study focuses on users' behaviors regarding information privacy protection technology adoption. According to our research results, users' online privacy protective behaviors positively affected by governmental regulations expressed as an information privacy protection law. In addition, if user is allowed to use anonymity when he or she uses online services, they have more tendencies to adopt privacy protection technologies. The detailed research findings and contribution are discussed as well.

• The Korean Journal of Archival Studies
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• no.52
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• pp.315-342
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• 2017

Language is an important medium for communication among the members of society and a mirror that reflects society as a whole. As society and culture change and develop over centuries, language follows suit. To keep up with the changes in the new era and express new concepts, countless new neologisms continue to appear. Recently, the use of neologisms is getting increasingly focused on social networking service and other Internet communication sites, which then spread rapidly through various media. If you look at the popular neologisms on the Internet, it implicitly reflects conflicts between the eras and the generations, people's psychology and ideology, and social phenomena such as culture. The function of neologisms is not solely for the entertainment element of communication but also for criticizing social problems and their vital use as a search keyword. This study focuses on the meaning and importance of gathering information and analyzing records about neologisms that reflect the social phenomenon in a certain period, and this will be labeled as "neologism archiving." This study proposes a direction for the construction of a neologism archive by comparing the currently existing neologism archiving system with the existing dictionary concept. In addition, this study serves as a reminder of the convenience and the contemporary social phenomena, such as smooth communication between generations, and the dissemination of inequality of information sharing. Lastly, this study aims to support experts with their research on neologisms for the social phenomenon.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.5
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• pp.93-106
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• 2006

With the rapid growth of the wireless Internet communication, a new generation of mobile devices have made possible the broad distribution of mobile digital contents, such as image, music, video, games and applications over the wireless Internet. Mobile devices are rapidly becoming the major means to extend communication channels without copy Protection, usage rule controlling and authentication. As a result, mobile digital contents may be illegally altered, copied and distributed among unauthorized mobile devices. In this paper, we take a look at Open Mobile Alliance (OMA) DRM v2.0 in general, its purpose and function. The OMA is uniquely the focal point for development of an open standard for mobile DRM. Next we introduces features for an active content and illustrates the difference between an active content and an inactive content. Enabling fast rendering of an active content, we propose an OMA-based DRM framework. This framework include the following: 1) Extending DCF Header for supporting an selective encryption, 2) Content encryption key management, 3) Rendering API for an active content. Experimental results show that the proposed framework is able to render an active content fast enough to satisfy Quality of Experience. %is framework has been proposed for a mobile device environment, but it is also applicable to other devices, such as portable media players, set-top boxes, or personal computer.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2169-2190
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• 2022

The COVID-19 pandemic has affected many aspects of human life. The pandemic not only caused millions of fatalities and problems but also changed public sentiment and behavior. Owing to the magnitude of this pandemic, governments worldwide adopted full lockdown measures that attracted much discussion on social media platforms. To investigate the effects of these lockdown measures, this study performed sentiment analysis and latent Dirichlet allocation topic modeling on textual data from Twitter published during the three lockdown waves in Malaysia between 2020 and 2021. Three lockdown measures were identified, the related data for the first two weeks of each lockdown were collected and analysed to understand the public sentiment. The changes between these lockdowns were identified, and the latent topics were highlighted. Most of the public sentiment focused on the first lockdown as reflected in the large number of latent topics generated during this period. The overall sentiment for each lockdown was mostly positive, followed by neutral and then negative. Topic modelling results identified staying at home, quarantine and lockdown as the main aspects of discussion for the first lockdown, whilst importance of health measures and government efforts were the main aspects for the second and third lockdowns. Governments may utilise these findings to understand public sentiment and to formulate precautionary measures that can assure the safety of their citizens and tend to their most pressing problems. These results also highlight the importance of positive messaging during difficult times, establishing digital interventions and formulating new policies to improve the reaction of the public to emergency situations.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.127-134
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• 2022

Steganography is a hidden technique in which secret messages are hidden in various multimedia files, and it is widely exploited for cyber crime and attacks because it is very difficult for third parties other than senders and receivers to identify the presence of hidden information in communication messages. Botnet typically consists of botmasters, bots, and C&C (Command & Control) servers, and is a botmasters-controlled network with various structures such as centralized, distributed (P2P), and hybrid. Recently, in order to enhance the concealment of botnets, research on Stego Botnet, which uses SNS platforms instead of C&C servers and performs C&C communication by applying steganography techniques, has been actively conducted, but image or video media-oriented stego botnet techniques have been studied. On the other hand, audio files such as various sound sources and recording files are also actively shared on SNS, so research on stego botnet based on audio steganography is needed. Therefore, in this study, we present the results of comparative analysis on hidden capacity by file type and tool through experiments, using a stego botnet that performs C&C hidden communication using audio files as a cover medium in Telegram Messenger.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.21-33
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• 2022

Recently, the recommender system has been widely used in various fields such as movies, music, online shopping, and social media, and in the meantime, the recommender model has been developed from correlation analysis through the Apriori model, which can be said to be the first-generation model in the recommender system field. In 2005, many models have been proposed, including deep learning-based models, which are receiving a lot of attention within the recommender model. The recommender model can be classified into a collaborative filtering method, a content-based method, and a hybrid method that uses these two methods integrally. However, these basic methods are gradually losing their status as methodologies in the field as they fail to adapt to internal and external changing factors such as the rapidly changing user-item interaction and the development of big data. On the other hand, the importance of deep learning methodologies in recommender systems is increasing because of its advantages such as nonlinear transformation, representation learning, sequence modeling, and flexibility. In this paper, among deep learning methodologies, RNN, CNN, and GAN-based models suitable for sequential modeling that can accurately and flexibly analyze user-item interactions are classified, compared, and analyzed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.37-50
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• 2023

This study aimed to examine the influence of a weight loss reality show watching on viewers' psychology and viewing effects by explicitly focusing on the Chinese TV show, Wow! Nice Figure (2019). Chinese women who had experience viewing Chinese TV show, Wow! Nice Figure and an experience of weight loss were the subject of the current study. The data collected from a total of 201 Chinese women were examined. Six variables; age, monthly income, occupation, education, BMI(Body Mass Index), and weight loss experience were included as control variables, and the data were analyzed with the use of SPSS 20.0. The results revealed that both simple and social viewing had been found to impact viewers' psychological attitudes positively. However, it was supported that simple and social viewing does not directly affect viewing satisfaction. Furthermore, the mediated effect of psychological variables within the relationship between simple viewing and viewing satisfaction and the relationship between social viewing and viewing satisfaction was investigated. From this study's results, the enhanced understanding of the impact of simple viewing, social viewing, and viewer's psychology on viewing satisfaction could be discussed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.175-183
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• 2023

In a broadcasting market environment that has a close interdependence between platform operators and content operators, problems such as conflicts over program usage fees, and home shopping transmission fees are intensifying. This study attempted to analyze the environment of the domestic broadcasting market and present implications, analyze the cause of user fee conflict between the platform and PP, and propose detailed alternatives to resolve user fee conflict disputes. The results of environmental analysis on the domestic broadcasting market are as follows. First, the growth engine of the broadcasting industry has changed to direct resources such as service usage fees and content fees, and commerce is increasing. Second, as hegemony in the domestic broadcasting market changes from terrestrial to paid broadcasting and OTT, monopolies in the entire broadcasting area are being dismantled by voluntary entry. Third, the need to overhaul the existing regulatory system is increasing due to the dismantling and reorganization of the existing broadcasting market. On the other hand, this study proposed a strategy to diversify the profit structure of PP, supply program after pre-contracting, and strengthen CPS bargaining power in order to resolve disputes between paid broadcasting platforms and PP sharply. In particular, as strategies to strengthen CPS bargaining power of small and medium-sized SOs, it proposed to jointly improve CPS-related systems through IPTV and individual SOs, to redefine fees for programs and to voluntarily use programs.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.1-28
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• 2022

In recent years, many Internet giants have begun providing their own content services, which attract online users by offering personalized services based on artificial intelligence technologies. This study investigates the role of two firms' content services within the firms' online service network. We examine the role of Naver Webtoon, which can be characterized as a professional-generated content, within Naver's service portfolio, and that of Google YouTube, which can be characterized as a user-generated content, within Google's service portfolio. Using survey data on viewers' use of the two services, we analyze a valued directed service network, where a node denotes an online service and a relationship between two nodes denotes a sequential use of two services. We found that both Webtoon and YouTube show higher out-degree centrality than in-degree centrality, which implies these content services are more likely to be starting services rather than arriving services within the firms' interactive network. The gap between the out-degree and in-degree centrality of YouTube is much smaller than that of Webtoon. The high centrality of YouTube, a user-generated content service, within the Google service network shows that YouTube's initial role of providing specific-content videos (e.g., entertainment) has expanded into a general search service for users.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.81-89
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• 2023

In modern society, blind people face difficulties in navigating common environments such as sidewalks, elevators, and crosswalks. Research has been conducted to alleviate these inconveniences for the visually impaired through the use of visual and audio aids. However, such research often encounters limitations when it comes to practical implementation due to the high cost of wearable devices, high-performance CCTV systems, and voice sensors. In this paper, we propose an artificial intelligence fusion algorithm that utilizes low-cost video sensors integrated into smartphones to help blind people safely navigate their surroundings during walking. The proposed algorithm combines motion capture and object detection algorithms to detect moving people and various obstacles encountered during walking. We employed the MediaPipe library for motion capture to model and detect surrounding pedestrians during motion. Additionally, we used object detection algorithms to model and detect various obstacles that can occur during walking on sidewalks. Through experimentation, we validated the performance of the artificial intelligence fusion algorithm, achieving accuracy of 0.92, precision of 0.91, recall of 0.99, and an F1 score of 0.95. This research can assist blind people in navigating through obstacles such as bollards, shared scooters, and vehicles encountered during walking, thereby enhancing their mobility and safety.