• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.206-208
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• 2022

As the big data industry has recently developed significantly, interest in privacy violations caused by personal information leakage has increased. There have been attempts to automate this through named entity recognition in natural language processing. In this paper, named entity recognition data is constructed semi-automatically by identifying sentences with de-identification information from de-identification information in Korean Wikipedia. This can reduce the cost of learning about information that is not subject to de-identification compared to using general named entity recognition data. In addition, it has the advantage of minimizing additional systems based on rules and statistics to classify de-identification information in the output. The named entity recognition data proposed in this paper is classified into twelve categories. There are included de-identification information, such as medical records and family relationships. In the experiment using the generated dataset, KoELECTRA showed performance of 0.87796 and RoBERTa of 0.88.

• Journal of the Health Care and Life Science
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• v.10 no.2
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• pp.253-258
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• 2022

It is a widely known fact that MAC addresses can be collected using Wi-Fi from mobile phones that people carry. However, since collecting and using MAC addresses without individual consent entails many legal problems, it was difficult to actively utilize them. In order to prevent invasion of privacy information due to unintentional exposure of these MAC addresses in recent years, the method of protecting privacy information by exposing a randomly generated virtual MAC address rather than the MAC address of the actual device is applied to all mobile devices. is becoming By exposing a randomly generated virtual MAC address on a device, it becomes impossible to identify and track an individual using the MAC address. However, the fact that various facts can be estimated through MAC Address collection is still valid. By expanding the application of Random MAC Address, the possibility of invasion of privacy information has been completely removed from the MAC address that has been raised in the past, so that it can be used more actively than in the past. In this paper, we propose a method for automatically collecting and analyzing statistical information of hospital visitors using MAC addresses. The collection of hospital visitors using MAC Address is a low cost and relatively accurate method, and the analysis of hospital visitors through steady collection can provide very objective and scientific evidence for hospital operation.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.176-183
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• 2021

Digital medical technology is very effective and at the same time faces the challenge of protecting privacy. However, for contact tracking and exposure notification apps in COVID-19 environment, there is always a trade-off between privacy measures and the effectiveness of the app's use. Today, many countries have developed and used contact tracking and exposure notification apps in various forms to prevent the spread of COVID-19, but the suspicion of digital surveillance (digital panopticon) is unavoidable. Therefore, this study aims to identify the factors of personal information infringement and dissatisfaction through text mining analysis by extracting user reviews of "Self-Quarantine Safety Protection" in Korea. As a result of the text mining analysis, we derived four groups, 'Address recognition error', 'Exit warning error', 'Access error', and 'App. program error'. Since 'Address recognition error' and 'Exit warning error' can give the app users a strong perception that they are keeping under surveillanc by the app, transparent management of personal information protection and consent procedures related to personal information collection are required. In addition, if the other two groups are not corrected immediately due to an error in an app function or a program bug, the complaints of users can be maximized and a protest against the monitor can be raised.

• Journal of the Korean Society for information Management
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• v.29 no.4
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• pp.83-99
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• 2012

The present study surveyed 225 undergraduates to examine their social media use behaviors and their perceptions of usefulness, trustworthiness, and privacy of social media for seeking and sharing health information. 151 respondents reported using social media for health information while 74 reported not using it for health matters. Results show that the most popular medium were social Q&As, followed by blogs and social networking sites. Age, gender, school year, and the presence of a health problem were associated with the social media use behaviors. This study suggests the potential of social media as a desired channel for providing health information to undergraduates.

• Annual Conference of KIPS
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• 2018.10a
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• pp.208-211
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• 2018

과학기술, 정보통신과 같은 기술들이 발전함에 따라 혁신적인 기술들 또한 대거 등장하였다. 이러한 기술들을 기반으로 새로운 서비스들이 등장하여 사람들의 삶의 질 또한 꾸준히 향상되고 있다. 그러나 기술발전 이면에는 해킹, 바이러스, 취약점 공격과 같은 역기능들의 기술 또한 지속해서 발전하고 있다. 공격자들은 이러한 기술들을 이용하여 정보자산의 침해, 사이버 테러, 금전적인 피해와 같은 사회 문제를 꾸준히 일으키고 있으며, 기업적으로는 개인정보 유출 및 산업 기밀 유출과 같은 정보보안 사고 또한 꾸준히 발생하고 있다. 이와 같은 이유로 SIEM(Security Information & Event Management)은 24시간 365일 네트워크와 시스템에 대한 지속적인 모니터링을 통해 외부로부터의 침입이나 각종 바이러스 등에 대해 적절한 대책을 통해 고객의 자산을 보호한다. 따라서 본 논문에서는 과거에서부터 현재까지의 내부 네트워크 기술의 발전을 살펴본 후 정보보안 사고 및 이상징후 탐지를 위한 통합 보안시스템 로그 관리 솔루션인 SIEM의 시대적 변화와 솔루션 동향에 대해 살펴 보고자 한다.

• Journal of KIISE
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• v.45 no.3
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• pp.294-302
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• 2018

With the emergence of the new service industry due to the development of information and communication technology, cyber space risks such as personal information infringement and industrial confidentiality leakage have diversified, and the security problem has emerged as a critical issue. In this paper, we propose a behavior-based anomaly detection method that is suitable for real-time and large-volume data analysis technology. We show that the proposed detection method is superior to existing signature security countermeasures that are based on large-capacity user log data according to in-company personal information abuse and internal information leakage. As the proposed behavior-based anomaly detection method requires a technique for processing large amounts of data, a real-time search engine is used, called Elasticsearch, which is based on an inverted index. In addition, statistical based frequency analysis and preprocessing were performed for data analysis, and the DBSCAN algorithm, which is a density based clustering method, was applied to classify abnormal data with an example for easy analysis through visualization. Unlike the existing anomaly detection system, the proposed behavior-based anomaly detection technique is promising as it enables anomaly detection analysis without the need to set the threshold value separately, and was proposed from a statistical perspective.

• The Journal of Korean Institute of Information Technology
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• v.17 no.5
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• pp.105-116
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• 2019

Most of the public and private buildings in Korea are installing CCTV for crime prevention and follow-up action, insider security, facility safety, and fire prevention, and the number of installations is increasing each year. In the questionnaire conducted on the increasing CCTV, many reactions were positive in terms of the prevention of crime that could occur due to the installation, rather than negative views such as privacy violation caused by CCTV shooting. However, CCTV poses a lot of privacy risks, and when the image data is collected using the cloud, the personal information of the subject can be leaked. InseCam relayed the CCTV surveillance video of each country in real time, including the front camera of the notebook computer, which caused a big issue. In this paper, we introduce a system to prevent leakage of private information and enhance the security of the cloud system by processing the privacy technique on image information about a subject photographed through CCTV.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.619-628
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• 2022

Although face recognition and face generation have been growing in popularity, the privacy issues of using facial images in the wild have been a concurrent topic. In this paper, we propose a face editing network that can reduce privacy issues by generating face images with various properties from a small number of real face images and facial mask information. Unlike the existing methods of learning face attributes using a lot of real face images, the proposed method generates new facial images using a facial segmentation mask and texture images from five parts as styles. The images are then trained with our network to learn the styles and locations of each reference image. Once the proposed framework is trained, we can generate various face images using only a small number of real face images and segmentation information. In our extensive experiments, we show that the proposed method can not only generate new faces, but also localize facial attribute editing, despite using very few real face images.

• Journal of KIISE:Information Networking
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• v.30 no.2
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• pp.189-198
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• 2003

As people are damaged increasingly by personal information leakage, awareness about user privacy infringement is increasing. However, the existing DRM system does not support the protection of user's personal information because it is not necessary for the protection of copyrights. This paper is suggesting a license administration protocol which is more powerful to protect personal information in DRM. To protect the exposure of users identifier, this protocol uses temporary ID and token to guarantee anonymity and it uses a session key by ECDH to cryptography and Public-Key Cryptosystem for a message so that it can protect the exposure of personal information and user's privacy.

• Journal of Digital Contents Society
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• v.6 no.4
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• pp.267-272
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• 2005

The ubiquitous computing environment is a new paradigm that represents the future life and is expected to bring about great changes in IT and in the lives of individuals. However, since a good deal of information can be easily obtained and shared in the ubiquitous computing environment, problems such as a security threat and infringement of privacy are getting serious. The present study is intended to explore some ways to minimize such problems by introducing RFID technology in the ubiquitous computing environment. This study also examines the causes of violation of security and privacy that might occur in the RFID system and requirement for security. In addition it seeks possible technical solutions to those causes.