• Journal of Korea Society of Digital Industry and Information Management
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• 제12권4호
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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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2017년도 춘계학술대회
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• pp.750-753
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• 2017

Recently, the processing and utilization of big data, which is generated by the spread of smartphone, SNS, and the internet of things, is emerging as a new growth engine of ICT field. However, in order to utilize such big data, De-identification of personal information should be done. De-identification removes identifying information from a data set so that individual data cannot be linked with specific individuals. De-identification can reduce the privacy risk associated with collecting, processing, archiving, distributing or publishing information, thus it attempts to balance the contradictory goals of using and sharing personal information while protecting privacy. De-identified information has also been re-identified and has been controversial for the protection of personal information, but the number of instances where personal information such as big data is de-identified and processed is increasing. In addition, many de-identification guidelines have been introduced and a method for de-identification of personal information has been proposed. Therefore, in this study, we describe the big data de-identification process and follow-up management, and then compare and analyze de-identification methods. Finally we provide personal information protection issues and solutions.

• Electronics and Telecommunications Trends
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• 제35권6호
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• pp.88-96
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• 2020

As the usability and value of personal information increase, the importance of privacy protection has increased. In Korea, the scope of the use of pseudonymized personal information has increased because of revisions to the law. In the past, security technologies were used to safely store and manage personal information, but now, security technologies focused on usability are needed to safely use personal information. In this paper, we look at issues related to the de-identification and re-identification of personal information. Moreover, we examine the standards and techniques related to the de-identification of personal information.

• Proceedings of the IEEK Conference
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.435-437
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• 2004

This paper presents a personal identification method using teeth images. The method uses images for teeth expressions of anterior and posterior occlusion state and LDA-based technique. Teeth images give merits for recognition because teeth, rigid objects, cannot be deformed at the moment of image acquisition. In the experiments, personal identification for 12 people was successful. It was shown that our method can contribute to multi-modal authentication systems.

• Journal of Digital Convergence
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• 제17권11호
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• pp.127-136
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• 2019

In the social media, information that users share with service providers can be divided into personal identification information such as gender and age and privacy-related information such as photos and comments. However, previous works on IS and service management have shed relatively little light on the difference of information-sharing decisions depending on the type of information. This study examines information-sharing decisions by separating the two types of information. A structural equation modeling method is used to test the research model based on a sample of 350 Facebook in South Korea. Analysis results show that self-expression, trust, and perceived security had a significant positive effect on both user's intentions to give personal identification information and their intentions to give privacy-related information. However, privacy concerns negatively affected their intentions to give personal identification and intention to give privacy-related information. The analysis results confirm that there was no difference between decision-making processes about sharing personal identification information and ones about sharing privacy-related information.

• Proceedings of the Korea Information Processing Society Conference
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• 한국정보처리학회 2012년도 추계학술발표대회
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• pp.907-909
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• 2012

주민등록번호는 주민생활의 편익 증진과 행정사무의 적정한 처리를 목적으로 도입되었으나 인터넷의 발달과 함께 관행적이고 무분별하게 사용되어 왔다. 수집된 주민등록번호가 해킹 등의 유출사고로 명의도용 등 범죄에 악용될 우려가 커지자 이를 근본적으로 해결하기 위하여 2011년 방송통신위원회는 인터넷상 주민등록번호 수집 이용을 제한하는 법 제도적 정책을 추진하였다. 정보통신망법이 개정되어 주민등록번호의 사용이 제한되면서 사업자에게 본인확인, 연령확인 등 법률의무의 이행이나 고객의 분쟁조정 등 목적을 위해 주민등록번호를 대체할 본인확인수단이 필요하게 되었다. 본 논문에서는 주민등록번호를 이용자가 입력하지 않으며 보편적으로 사용하고 있는 인프라를 이용하고 단순한 입력정보의 변경을 통해 본인확인을 할 수 있는 방안을 제안한다.

• Journal of Multimedia Information System
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• 제4권4호
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• pp.263-270
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• 2017

Various security threats exist in the smart grid environment due to the fact that information and communication technology are grafted onto an existing power grid. In particular, smart metering data exposes a variety of information such as users' life patterns and devices in use, and thereby serious infringement on personal information may occur. Therefore, we are in a situation where a de-identification algorithm suitable for metering data is required. Hence, this paper proposes a new de-identification method for metering data. The proposed method processes time information and numerical information as de-identification data, respectively, so that pattern information cannot be analyzed by the data. In addition, such a method has an advantage that a query such as a direct range search and aggregation processing in a database can be performed even in a de-identified state for statistical processing and availability.

• Journal of Industrial Technology
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• 제24권A호
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• pp.59-65
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• 2004

Personal identification using fingerprints needs much calculational effort. Generally, there are various methods for fingerprint-based identification. In this paper, an identification method is proposed which is based on direction distribution of fingerprint ridges. An 8-directional Gabor filter bank is used for extracting the feature vector from the given fingerprint. Then, it is compared with those of registered fingerprints for matching. This method is simple and fast to implement because it uses the information of ridge directions only. An experiment on 532 fingerprints from NIST database and some other source shows its usefulness.

• Journal of Platform Technology
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• 제11권3호
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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 Korea Contents Association
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• 제16권11호
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• pp.11-19
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• 2016

The personal identification based on the biometrics has emerged as one of the new trend. This study attempted to explore and examine the user recognition in the use of the personal identification based on the biometrics in the respect of self-efficacy, trustiness, security, and safety alongside the effect of the recognition on the future use intention through survey. The result of this study demonstrated the effect on the use intention of the perceived trustiness and ease of the fingerprint identification, perceived ease of the iris identification and the perceived trustiness of the vein identification. The result of this study is expected to suggest direction on the application of the biometrics considering user recognition.