• Journal of Digital Convergence
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• v.11 no.11
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• pp.143-153
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• 2013

Big data is expected to bring forth enormous public good as well as economic opportunity. However there is ongoing concern about privacy not only from public authorities but also from private enterprises. Big data is suspected to aggravate the existing privacy battle ground by introducing new types of privacy risks such as privacy risk of behavioral pattern. On the other hand, big data is asserted to become a new way to by-pass tradition behavioral tracking such as cookies, DPIs, finger printing${\cdots}$ and etc. For it is not based on a targeted person. This paper is to find out if big data could contribute to catching out behavioral patterns of consumers without threatening or damaging their privacy. The difference between traditional behavioral tracking and big data analysis from the perspective of privacy will be discerned.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.87-92
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• 2014

We have noted a possibility of big data as a solution of social problem and pending issue. At the same time big data has a problem of privacy. Big data and privacy were in conflict. In this paper we pointed out that issue and propose a planning of big data based on privacy using case study of advanced country.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.1-12
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• 2016

Today, with the popularity of smart phones and the proliferation of SNS, anyone is exposed to the risk of personal information leakage. Unlike the prior studies of privacy, this research aims to identify the privacy factors affecting the provision intention of individual information from the SNS Users. This study also analyses how the perceived privacy risks and corporate trust affect the provision intention of individual information. The analysis results of empirical data show that despite experiencing the privacy leakage such as direct hacking and being aware of the risk, people are providing firms with personal information. The most influential variables to perceived privacy risk are information privacy policy, information privacy concern, previous privacy experience and information privacy awareness in the decreasing order of importance. Those to the corporate trust are information privacy policy, information privacy awareness, previous privacy concern and information privacy experience. Besides, the corporate trust and the perceived privacy risk also affect the provision intention of personal information. Finally, this study proposes the implications for personal information privacy.

• The Journal of Society for e-Business Studies
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• v.21 no.1
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• pp.131-145
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• 2016

This study built the theoretical frameworks for empirical analysis based on the analysis of the relationship among the concepts of risk of information privacy, the policy of information privacy via the provision studies. Also, in order to analyze the relationship among the factors such as the concern of information privacy, trust, intention to offer the personal information, this study investigated the concepts of information privacy and studies related with the privacy, and established a research model about the information privacy. Followings are the results of this study: First, the information privacy risk has the positive effects upon the information privacy concern and it has the negative effects upon the trust. Second, the information privacy policy has the positive effects upon the information privacy concern and it has the negative effects upon the trust. Third, the information privacy concern has the negative effects upon the trust. At last, the information privacy concern has the negative effects upon the provision intention of personal information and the trust has positive effects upon the offering intention of personal information.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.189-193
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• 2014

SNS (Social Network Service) has evolved to life-friendly service with the combination of local services. Unlike exsiting mobile services, life-friendly service is expected to be personalized with gathering of local information, location information and social network service information. In the process of gathering various kinds of information, Big-data technology and Cloud technology is needed. The effective algorithem has researched for this already, however the privacy protection model hasn't researched enough in life-friendly service or big-data using circumstance. In this paper, the privacy issue is dealt with in terms of 'Structure hole', and the privacy issue comes from big-data technology of life-friendly service.

• Informatization Policy
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• v.21 no.4
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• pp.20-39
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• 2014

The age of big data has not only opened new opportunities for economic growth in various industries, but it has also created new problems related to personal information protection and privacy invasion. Given this situation, Korea's communications commission has proposed a big data guideline that specifies how companies should collect and utilize personal information in the big data environment. However, this guideline is more focused on industrial development than personal information protection, and it contains many features that conflict with personal information protection law as it currently exists. As a result, civic groups strongly oppose the guideline, as it may create serious privacy issues for subjects of information gathering. Thus, this paper analyses the limitations of the guideline by comparing it with domestic and foreign laws about personal information protection and privacy. We also discuss the direction of legalization and institutionalization with respect to the secure use of big data.

• The Journal of Bigdata
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• v.3 no.2
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• pp.1-10
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• 2018

In the field of smart water management, there is an increasing demand for strengthening competitiveness through big data analysis. As a result, systematic management (Governance) of big data is becoming an important issue. Big data governance is a systematic approach to evaluating, directing and monitoring data management, such as data quality assurance, privacy protection, data lifetime management, data ownership and clarification of management rights. Failure to establish big data governance can lead to serious problems by using low quality data for critical decisions. In addition, personal privacy data can make Big Brother worry come true, and IT costs can skyrocket due to the neglect of data age management. Even if these technical problems are fixed, the big data effects will not be sustained unless there are organizations and personnel who are dedicated and responsible for data-related issues. In this paper, we propose a method of building data governance for smart water data management based on big data.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.49-58
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• 2019

In the era of the 4th industrial revolution, the development of information technology brought various benefits, but it also increased social interest in privacy issues. As the possibility of personal privacy violation by big data increases, academic discussion about privacy management has begun to be active. While the traditional view of privacy has been defined at various levels as the basic human rights, most of the recent research trends are mainly concerned only with the information privacy of online privacy protection. This limited discussion can distort the theoretical concept and the actual perception, making the academic and social consensus of the concept of privacy more difficult. In this study, we analyze the privacy concept that is exposed on the internet based on 12,000 news data of the portal site for the past one year and compare the difference between the theoretical concept and the socially accepted concept. This empirical approach is expected to provide an understanding of the changing concept of privacy and a research direction for the conceptualization of privacy for current situations.

• Informatization Policy
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• v.24 no.1
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• pp.79-99
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• 2017

Despite the early success story, the pan-industry diffusion of big data has been slow mostly due to lack of confidence of the value creation and privacy-related concerns. The problem leads us to the need to a stakeholder analysis on the adoption process of big data. The present study combines technology acceptance model, task-technology fit theory, and privacy calculus theory to integrate the positive and negative factors on the big data adoption. The empirical analysis was performed based on the survey from the current and potential big data users. Results revealed perceived usefulness, task-technology fit, and privacy concern are significant antecedents to the intention to use big data. Furthermore, there are significant differences in the perceptions of each constructs among groups divided by the types of big data use, with several exceptions. And the control effect was found in the magnitude of the relation between independent variables and dependent variable. The theoretical and politic implications of the analysis are discussed as to the promotion of big data industry.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.139-141
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• 2018

최근 IoT, SNS 등이 확대 되면서 대규모의 빅데이터가 생산되고 있고, 이러한 빅데이터는 AI 등 지능형 기술과 결합하여 다양한 분야의 예측과 의사결정을 지원하며 새로운 가치를 창출하고 있다. 그러나, 이러한 활용에 있어 가장 걸림돌이 되는 것은 빅데이터에 내제되어 있는 개인정보에 대한 위협이다. 본연구에서는 빅데이터에 내제되어 있는 개인정보를 보호하면서도 빅데이터의 효과적인 분석과 활용을 가능하게 할 수 있는 동형암호(homomorphic encryption)을 살펴보고 빅데이터의 프라이버시 강화 방안과 이를 통한 빅데이터의 활용방안에 대해 연구하고 향 후 과제 등에 대해 고찰해 보도록 한다.