• Smart Media Journal
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• v.10 no.2
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• pp.100-109
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• 2021

As the COVID-19 vaccination begins, it is necessary to safely store and manage the vaccination history for vaccinated people, as well as provide only the minimal information for the requested purpose, not in the form of all or nothing, to the institution requesting vaccination personal information. This paper proposes a scheme to safely store and manage the people's vaccination records in a non-forgeable blockchain, and to ensure that users provide only the minimal information necessary to the verifier from their vaccination personal information. A user authorizes the verifier to access the information he has consented with by entering the fingerprint on his smartphone, and in this process, no personal information or secrets can be exposed to an attacker. In addition, it is guaranteed that it is neither possible to impersonate the user nor to steal user personal information even in the case of theft or loss of the smartphone, or leakage of information from the vaccination history management institution. Using the scheme, users have no fear on external exposure of personal information and follow-up damage due to excessive information provision by giving out only the minimal information suited to the verifier.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.43-49
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• 2019

The wired and wireless Internet is a useful window to easily acquire various types of media data. On the other hand, the public can easily get the media data including the object to which the personal information is exposed, which is a social problem. In this paper, we propose a method to robustly detect a target object that has exposed personal information using a learning algorithm and effectively block the detected target object area. In the proposed method, only the target object containing the personal information is detected using a neural network-based learning algorithm. Then, a grid-like mosaic is created and overlapped on the target object area detected in the previous step, thereby effectively blocking the object area containing the personal information. Experimental results show that the proposed algorithm robustly detects the object area in which personal information is exposed and effectively blocks the detected area through mosaic processing. The object blocking method presented in this paper is expected to be useful in many applications related to computer vision.

• Smart Media Journal
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• v.12 no.3
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• pp.38-48
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• 2023

When an individual needs to prove eligibility, it is sufficient to know whether or not s/he meets the eligibility, but any existing method inevitably exposes the identity of the owner or unnecessary additional information in the process of providing personal information. In this paper, among the immutable items of personal information such as gender, date of birth, and place of birth, we propose a method in which the owner provides only essential item(s) to the eligibility verifier with each iterm marked on one option among multiple choices. In this way, the eligibility verifier can access the combination of items stored in the blockchain with the consent of the information owner, and can safely store the access history by requesting recording in the blockchain again. In the proposed method, the user does not worry about his/her identity being revealed or his/her personal information being overly exposed, and the eligibility verifier can check only necessary items and search later records without separately storing the records.

• Knowledge Management Research
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• v.25 no.1
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• pp.1-19
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• 2024

This study analyzed the changes in social media reactions of data subjects to major personal data breach incidents in South Korea from January 2014 to October 2022. We collected a total of 1,317 posts written on Naver Blogs within a week immediately following each incident. Applying the LDA topic modeling technique to these posts, five main topics were identified: personal data breaches, hacking, information technology, etc. Analyzing the temporal changes in topic distribution, we found that immediately after a data breach incident, the proportion of topics directly mentioning the incident was the highest. However, as time passed, the proportion of mentions related indirectly to the personal data breach increased. This suggests that the attention of data subjects shifts from the specific incident to related topics over time, and interest in personal data protection also decreases. The findings of this study imply a future need for research on the changes in privacy awareness of data subjects following personal data breach incidents.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.5
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• pp.95-111
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• 2021

This paper is a study to check the flow of how addiction to media services has been studied from a long-term perspective, and to identify variables that can be the basis for future addiction research. Researchers noted the addiction of media services in adolescents in particular, and identified a combination of factors depending on the background of the times. Addiction variables were largely aggregated into four properties: adolescent properties, personal properties, media properties, and media-dependent properties. Addiction variables belonging to the attribute were influenced by major media and divided into four periods. During the study period, the frequency of variables was most related to personal attributes, followed by media attributes, adolescent attributes, and media-dependent attributes. Also Individual attribute variables gradually shifted from object-relationship to individual psychological factors. Variants in media attributes were influenced by the introduction and spread of new media. Variations in adolescent and media-dependent attributes have been weak in studies that observe teenagers' motivations for media use or are related to addiction, and no papers have been published since 2020. Although addiction research on media services is important in terms of industry, there has been an emphasis on social aspects, based on the results of this study, we hope to continue to study the variables of service users who can be used in terms of industry.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.11a
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• pp.161-163
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• 2017

다양한 연령층에서 시청자가 늘어나고 있는 개인방송에서도 VR 서비스가 확대되고 있다. 기존의 VR 방송은 360도 카메라로 촬영된 영상을 시청자들이 VR로 보거나 개인방송 크리에이터들이 HMD를 착용하고 콘텐츠를 플레이 하는 영상을 시청자들이 시청하도록 구성되어있다. 시청자들의 몰입감과 흥미를 더욱 유발하기 위해 본 논문에서는 시청자의 입장에서 크리에이터가 진행하는 방송도 시청할 수 있고, 그 콘텐츠를 직접 즐길 수 있는 선택적 방송 시스템을 제안한다. 제안된 시스템은 기존의 시스템보다 시청자로 하여금 몰임감을 향상시키고 참여 한계를 극복할 수 있다.

• International Journal of Contents
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• v.17 no.4
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• pp.35-45
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• 2021

In this study, we analyzed the factors that affect public awareness campaigns on social media platforms and developed an integrated model for measuring the persuasiveness of environmental social media campaigns. A survey questionnaire was created and distributed on Facebook with the goal of reaching individuals in their 20s and 40s in Vietnam, and 395 valid replies were gathered. The findings showed that the STOPS was reconfirmed as a suitable theoretical framework for analyzing the public's behaviour intention to conduct information related to the issue of fine dust, especially on social media. Furthermore, it also showed that social media efficacy has a moderating effect on the relationship between public's situational recognition and informational behaviour intention. This suggested that through social media platforms, personal characteristics play a vital part in developing effective environmental campaigns. Implications for both theory and practice were discussed.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.263-264
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• 2008

고속 무선 PAN(Personal Area Networks)기술은 10m 이내의 짧은 거리에서 고속으로 대용량의 데이터를 전송하기 위한 기술로, 최근 무선 USB(Wireless Universal Serial Bus)나 HDTV(High Definition TV)와 같은 광대역 멀티미디어 응용 시장을 겨냥한 연구가 IEEE 802.15.3과 WiMedia를 중심으로 활발히 진행되고 있다. [1] 본 논문에서는 WiMedia Alliance에서 제안한 Distributed Medium Access Control (D-MAC)에서 다수 스트림의 QoS 요구를 만족시키는 신뢰성 있는 전송을 위해 데이터 시간 슬롯을 효율적으로 할당하는 알고리즘에 대해 연구하고자 한다.

• Smart Media Journal
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• v.13 no.4
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• pp.9-15
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• 2024

Tree-based algorithms have been the dominant methods used build a prediction model for tabular data. This also includes personal credit data. However, they are limited to compatibility with categorical and numerical data only, and also do not capture information of the relationship between other features. In this work, we proposed an ensemble model using the Transformer architecture that includes text features and harness the self-attention mechanism to tackle the feature relationships limitation. We describe a text formatter module, that converts the original tabular data into sentence data that is fed into FinBERT along with other text features. Furthermore, we employed FT-Transformer that train with the original tabular data. We evaluate this multi-modal approach with two popular tree-based algorithms known as, Random Forest and Extreme Gradient Boosting, XGBoost and TabTransformer. Our proposed method shows superior Default Recall, F1 score and AUC results across two public data sets. Our results are significant for financial institutions to reduce the risk of financial loss regarding defaulters.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.51-58
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• 2016

In the area of hotel and tourism sector, various research are analyzed using big data. Big data is being generated by any digital devices around us all the times. All the digital process and social media exchange produces the big data. In this paper, we analyzed the de-identification method of big data to use the personal information of hotel guests. Through the analysis of these big data, hotel can provide differentiated and diverse services to hotel guests and can improve the service and support the marketing of hotels. If the hotel wants to use the information of the guest, the private data should be de-identified. There are several de-identification methods of personal information such as pseudonymisation, aggregation, data reduction, data suppression and data masking. Using the comparison of these methods, the pseudonymisation is discriminated to the suitable methods for the analysis of information for the hotel guest. Also, among the pseudonymisation methods, the t-closeness was analyzed to the secure and efficient method for the de-identification of personal information in hotel.