• Journal of the Korea Computer Industry Society
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• v.2 no.10
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• pp.1245-1252
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• 2001

In this paper, we have identified speakers who give digits in Korean. In order to identify speakers, we have utilized the specifie feature parameters which extracted from sound wave. We have noticed that multipulses are present in pitch periods of sound wave, which containes the personal information and depends on the speakers. In this experiment, we have extracted multipulses, and have attempted to identify the speaker by investigating the specific feature parameters of each speaker based on the extracted multipulses.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.1018-1021
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• 2020

최근 개인정보가 포함된 비정형 텍스트 문서들이 유출되거나 무분별하게 공개됨으로써 정보의 주체는 물론 기업들까지 피해를 받고 있다. 데이터를 공개 및 활용하기 위해 개인정보 검출 및 비식별화 과정이 필수적이지만 정형 데이터와는 달리 비정형 데이터의 경우 해당 과정을 자동으로 처리하는 데 한계가 있다. 이를 위해 딥러닝 모델들을 사용하여 자동화하려는 연구들이 있었지만 문장 내 단어의 모호성에 대한 고려 없이 단어 개체명 정보에만 의존하여 개인정보를 검출하는 형태로 진행되었다. 따라서 문장 내 단어들 중 식별 대상인 단어들도 비식별화 되어 데이터에 대한 유용성을 저해할 수 있다는 문제점을 남겼다. 본 논문에서는 문장의 의도 정보를 단어의 개체명 학습 과정에 부가적인 정보로 활용하는 개인정보 검출 모델과 개인정보 데이터의 유용성을 고려한 비식별화 기법을 제안한다.

• 정보보호뉴스
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• s.138
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• pp.58-59
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• 2009

사회가 발전함에 따라 개인정보의 의미는 인격권과 재산권이 혼재된 새로운 의미로 그 범위가 확대되고 있다. 개인정보의 범위에는 SMS, 음성통화 내역, 사진, 영상 등 개인을 식별해 프라이버시를 침해할 수 있는 정보를 비롯해 마케팅에 활용 가능한 주민등록번호, 계좌번호, 카드번호, 거래내역, 신용정보 즉, 경제적인 효용(편익)을 얻기 위해 기업에게 제공하는 식별정보 등이 모두 개인정보에 포함된다. 최근 발생한 일련의 개인정보 유출사고와 법적 공방은 개인과 관련된 다양한 정보를 보호하기 위해 기업이 추가적인 조치가 필요하다는 것을 의미한다. 하지만 기업이 개인정보를 보호하기 위해서는 기존 방화벽으로 대표되는 외부와 내부를 차단하는 보안에 대한 관점 및 체계로는 한계를 지닌다.

• Journal of Platform Technology
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• v.11 no.3
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• pp.56-67
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• 2023

Recently, de-identification of personal information, which has been a long-cherished desire of the data-based industry, was revised and specified in August 2020. It became the foundation for activating data called crude oil[2] in the fourth industrial era in the industrial field. However, some people are concerned about the infringement of the basic rights of the data subject[3]. Accordingly, a development study was conducted on the Batch De-Identification Tool, a personal information de-identification automation tool. In this study, first, we developed an image labeling tool to label human faces (eyes, nose, mouth) and car license plates of various resolutions to build data for training. Second, an object recognition model was trained to run the object recognition module to perform de-identification of personal information. The automated personal information de-identification tool developed as a result of this research shows the possibility of proactively eliminating privacy violations through online services. These results suggest possibilities for data-based industries to maximize the value of data while balancing privacy and utilization.

• The Journal of the Convergence on Culture Technology
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• v.2 no.4
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• pp.71-76
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• 2016

In this study, de-identification policies of the US, the UK, Japan, China and Korea are compared to suggest a future direction of de-identification regulations and a method for vitalizing the big data industry. Efficiently using the de-identification technology and the standard of adequacy evaluation contributes to using personal information for the industry to develop services and technology while not violating the right of private lives and avoiding the restrictions specified in the Personal Information Protection Act. As a counteraction, the re-identification issue may occur, for re-identifying each person as a de-identified data collection. From the perspective of business, it is necessary to mitigate schemes for discarding some regulations and using big data, and also necessary to strengthen security and refine regulations from the perspective of information security.

• Review of KIISC
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• v.29 no.4
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• pp.13-18
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• 2019

우리나라 정부는 2016년, 현행 개인정보보호 법령의 틀 내에서 데이터가 안전하게 활용될 수 있도록 관계부처 합동 <개인정보 비식별 조치 가이드라인>을 마련하여, 비식별 조치를 위해 사업자 등이 준수해야 할 비식별 조치 기준을 제시하였다. 그 후 국내에서는 조화로운 방향으로 개인정보보호와 활용을 이루기 위해 다양한 노력이 있었고 이와 관련하여, 본고에서는 국내 비식별 조치 추진현황 및 2016년 이후 한국 주도로 개발 중인 국제표준 2건 등 비식별 처리 분야의 국제표준화 동향을 살펴본다.

• Convergence Security Journal
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• v.19 no.5
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• pp.75-84
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• 2019

Recently, the value of video as an important data of medical information technology is increasing due to the feature of rich clinical information. On the other hand, video is also required to be de-identified as a medical image, but the existing methods are mainly specialized in the stereotyped data and still images, which makes it difficult to apply the existing methods to the video data. In this paper, we propose an automated system to index candidate elements of personal identification information on a frame basis to solve this problem. The proposed system performs indexing process using text and person detection after preprocessing by scene segmentation and color knowledge based method. The generated index information is provided as metadata according to the purpose of use. In order to verify the effectiveness of the proposed system, the indexing speed was measured using prototype implementation and real surgical video. As a result, the work speed was more than twice as fast as the playing time of the input video, and it was confirmed that the decision making was possible through the case of the production of surgical education contents.

• The Journal of Society for e-Business Studies
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• v.24 no.1
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• pp.121-137
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• 2019

De-identification is a method by which the remaining information can not be referred to a specific individual by removing the personal information from the data set. As a result, de-identification can lower the exposure risk of personal information that may occur in the process of collecting, processing, storing and distributing information. Although there have been many studies in de-identification algorithms, protection models, and etc., most of them are limited to structured data, and there are relatively few considerations on de-identification of unstructured data. Especially, in the medical field where the unstructured text is frequently used, many people simply remove all personally identifiable information in order to lower the exposure risk of personal information, while admitting the fact that the data utility is lowered accordingly. This study proposes a new method to perform de-identification by applying the k-anonymity protection model targeting unstructured text in the medical field in which de-identification is mandatory because privacy protection issues are more critical in comparison to other fields. Also, the goal of this study is to propose a new utility metric so that people can comprehend de-identified data set utility intuitively. Therefore, if the result of this research is applied to various industrial fields where unstructured text is used, we expect that we can increase the utility of the unstructured text which contains personal information.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.355-358
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• 2021

개인의 신원정보 보호에 대한 중요성이 높아지면서 개인이 직접 자신의 신원정보를 관리하고 데이터의 주권을 신원정보 소유자에게 부여하는 자기주권 신원 시스템에 대한 관심이 높아지고 있다. 자기주권 신원 시스템 내에서 개인은 스스로 자신을 식별할 수 있는 분산 식별자(DID: decentralized identifier)를 생성하고 분산 식별자 별 개인의 자격을 증명해주는 자격증명(VC: verifiable credentials) 정보를 발급받아 개인이 보유하며 자격증명의 검증을 요구하는 검증자에게 선택적으로 자격증명 정보를 제시한다. 개인의 프라이버시를 보호하기 위해 개인의 자격증명을 제시할 때 신원정보의 실제 데이터는 감추고 자격증명의 유효성은 입증시키는 영지식 증명의 개념을 적용하고 있다. 본 논문에서는 영지식 증명 기술을 살펴보고 하이퍼레저 인디(Hyperledger Indy) 기반 자기주권 신원 시스템에서 영지식 증명 기술 도입 예를 보인다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.3
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• pp.91-101
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• 2011

Internet is becoming increasingly popular due to the rapid development of information and communication technology. There has been a convenient social activities such as the mutual exchange of information, e-commerce, internet banking, etc. through cyberspace on a computer. However, by using the convenience of the internet, the personal IDs(identity card, driving license, passport, student ID, etc.) represented by the electronic media are exposed on the internet frequently. Therefore, this study propose a feature extraction method to analyze the characteristics of image files containing personal information and a image retrieval method to find the images using the extracted features. The proposed method selects the feature information from color, texture, and shape of the images, and the images as searched by similarity analysis between feature information. The result which it experiments from the image which it acquires from the web-based image DB and correct image retrieval rate is 89%, the computing time per frame is 0.17 seconds. The proposed method can be efficiently apply a system to search the image files containing personal information and to determine the criteria of exposure of personal information.