• Informatization Policy
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• v.28 no.1
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• pp.64-76
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• 2021

The purposes of this study are to identify factors that affect personal information protection activities from the perspective of personal information managers and explore ways of promoting such activities. The main factors examined by threat and response assessments were selected based on the protection motivation theory, and the effects of each factor were analyzed using a multinomial logit model. The analysis results show that small-scale personal information managers need to be provided with both educational support to enhance their awareness and technical support, such as protection inspection tools, to help them carry out their own personal information protection activities. Personal information managers larger than a certain size also require tax support, including tax cuts, to support their budgets for and investments in personal information protection activities. In addition, they need professional education that emphasizes practice.

• 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.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.5
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• pp.1269-1277
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• 2016

European Union and United States have introduced new Privacy Shield agreement after decision of Court of Justice of the European Union which invalidated Safe Harbor agreement. Privacy Shield agreement contains several clauses to raise the level of personal data protection such as enhanced commitments, stronger enforcement, clear safeguards and transparency obligations, and effective protection of EU citizens' rights with several redress possibilities. This agreement has received positive response as an enhanced measure for personal data protection. This paper examines EU and US discussion history and current situation regarding Privacy Shield and suggests national policy direction such as measures for personal data transborder flow system improvement and international cooperation.

• The Journal of Information Systems
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• v.30 no.4
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• pp.203-226
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• 2021

Purpose The purpose of this study is to enhance the accuracy score of personal credit scoring using the convolutional neural networks and secure the transparency of the deep learning model using eXplainalbe Artifical Inteligence(XAI) technique. Design/methodology/approach This study built a classification model by using the convolutional neural networks(CNN) and applied a methodology that is transformation of numerical data to imaged data to apply CNN on personal credit data. Then layer-wise relevance propagation(LRP) was applied to model we constructed to find what variables are more influenced to the output value. Findings According to the empirical analysis result, this study confirmed that accuracy score by model using CNN is highest among other models using logistic regression, neural networks, and support vector machines. In addition, With the LRP that is one of the technique of XAI, variables that have a great influence on calculating the output value for each observation could be found.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.4
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• pp.258-262
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• 2017

The PCA(Principal Component Analysis) algorithm is widely used as a technique of expressing the eigenvectors of the covariance matrix that best represents the characteristics of the data and reducing the high dimensional vector to a low dimensional vector. In this paper, we have developed a personal authentication method based on ECG using principal component analysis. The proposed method showed excellent recognition performance of 98.2 [%] when it was experimented using electrocardiogram data obtained at weekly intervals. Therefore, it can be seen that it is useful for personal authentication by reducing the dimension without changing the information on the variability and the correlation set variable existing in the electrocardiogram data by using the principal component analysis technique.

• Korean Journal of Computational Design and Engineering
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• v.21 no.3
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• pp.215-223
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• 2016

The low price around 1000 USD makes consumer 3D printers as a new additive manufacturing platform for the personal manufacturing where consumers can make and sell their own products. To allow the consumers to design and manufacture their products, not only economic 3D printers but also supporting information systems for their design and manufacturing are essential. This study suggests an extended product data management (PDM) system that can support both the design and manufacturing of personal products with consumer 3D printing services. This extended PDM system helps consumer designers use advanced PDM technologies for their design and connected 3D printing services with Internet of Things (IoT) technology for realization of their products. As a result, the proposed system supports the consumer designers a seamless integrated product development and manufacturing environment supported by PDM and consumer 3D printing services.

• Informatization Policy
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• v.26 no.1
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• pp.25-45
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• 2019

With the advent of the data economy, interest in using big data has increased, but conflicts with protecting personal information have been also steadily raised. In this regard, major countries are accelerating use of big data by exempting de-identified, pseudonymous personal information from protection. However, these policies have been made without the understanding that the economic value of personal information has been actually changing slowly. This paper presents the concept of 'collected information' and defines it as having public interest and therefore, not the exclusive property of the collector of such information. The paper shows the collected information has public interest in terms of personal information protection, connectivity, and universal service and public goods. It also specifies that the 'data governance' cannot be applied to the current data utilization framework that depends upon the holder's consent; rather, it raises the need to improve the practices of information provision consent or provide the beneficiary right of information use to the information holder in order to ensure the proper 'data governance' that will turn market failure into success.

• Convergence Security Journal
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• v.19 no.5
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• pp.63-73
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• 2019

In the 4th Industrial Revolution, information is collected and analyzed from people and objects through the rapid development of ICT. It is possible to create value. However, there are many legal and institutional restrictions on the collection of information aimed at people.Therefore, in-depth research on the protection and use of personal information in the rapidly changing cyber security environment is needed. The purpose of this study is to protect and utilize personal information for the operation of AI (Artificial Intelligence) and big data during the 4th Industrial Revolution. It is to seek a paradigm shift. The organization of the research for this is: Chapter 1 examines the meaning of personal information during the 4th Industrial Revolution, Chapter 2 presents the framework for the review and analysis of prior research. In Chapter 3, after analyzing policies for the protection and utilization of personal information in major countries, Chapter 4 looks at the paradigm shift in personal information protection during the 4th Industrial Revolution and how to respond. Chapter 5 made some policy suggestions for the protection and utilization of personal information.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.2
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• pp.59-66
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• 2019

The emergence of new IT technologies and convergence industries, such as artificial intelligence, bigdata and the Internet of Things, is another chance for South Korea, which has established itself as one of the world's top IT powerhouses. On the other hand, however, privacy concerns that may arise in the process of using such technologies raise the task of harmonizing the development of new industries and the protection of personal information at the same time. In response, the government clearly presented the criteria for deidentifiable measures of personal information and the scope of use of deidentifiable information needed to ensure that bigdata can be safely utilized within the framework of the current Personal Information Protection Act. It strives to promote corporate investment and industrial development by removing them and to ensure that the protection of the people's personal information and human rights is not neglected. This study discusses the strategy of deidentifying personal information protection based on the analysis of fake news. Using the strategies derived from this study, it is assumed that deidentification information that is appropriate for deidentification measures is not personal information and can therefore be used for analysis of big data. By doing so, deidentification information can be safely utilized and managed through administrative and technical safeguards to prevent re-identification, considering the possibility of re-identification due to technology development and data growth.

• Journal of Multimedia Information System
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• v.4 no.4
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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.