• Journal of Digital Convergence
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• v.19 no.10
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• pp.151-161
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• 2021

This study has investigated how social exclusion affects privacy concerns and intention to provide personal information. And to examine the moderating effect of perceived sense of control in the process. As a result, it was found that social exclusion increases users' privacy concerns and reduces the intention to provide personal information. In addition, it was verified that the moderating effect of social exclusion on the privacy concerns and intention to provide personal information was significant. In other words, it was proved that sense of control can reduce the influence on privacy concerns and personal information provision intentions due to social exclusion. The results of this research suggest that social exclusion can act as a factor influencing privacy concerns and intention to provide personal information, and that perceived control can reduce the effect of social exclusion. In conclusion, the results of this study suggest that individual psychological factors should be considered as influencing variables in privacy research.

• Journal of KIISE
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• v.44 no.9
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• pp.918-931
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• 2017

Recently, the spread of smartphones and various wearable devices has led to increases in the accumulation and usage of personal information. As a result, privacy protection has become an issue. Even though there have been studies and efforts to improve legal and technological security measures for protecting privacy, personal information leakage accidents still occur. Rather than privacy requirements, analysts mostly focus on the implementation of security technology within software development. Previous studies of security requirements strongly focused on supplementing the basic principles and laws for privacy protection and securing privacy requirements without understanding the relationship between privacy and security. As a result, personal information infringement occurs continuously despite the development of security technologies and the revision of the Personal Information Protection Act. Therefore, we need a method for eliciting privacy requirements based on related privacy protection laws that are applicable to software development. We also should clearly specify the relationship between privacy and security. This study aims to elicit privacy requirements and create privacy assurances cases for Privacy Friendly System development.

• Journal of the Korean Home Economics Association
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• v.46 no.2
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• pp.59-71
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• 2008

The purpose of this study was to discuss the role of mothers in children's privacy protection on the Internet. Specifically, the study explored 1)children's privacy protection efforts on the Internet, 2)types of personal information children provided at Web sites, and 3)the effect of mothers' privacy protection efforts on their children's privacy protection levels. The Internet survey was conducted and total of 153 mothers and their children aged 12-13 were included for statistical analysis. The descriptive statistics and Ordinary Least Squares were used. The results yield that children showed relatively high levels in providing personal information on the Internet, while they have no sufficient competency at privacy protection. The effect of mothers' privacy protection efforts on children's privacy protection was partially supported. The longer hours of Internet use and frequent participation in online events increased the potential consequences of children's privacy invasion. Providing privacy standards for online service providers and marketers targeting children could help protect children's privacy. Moreover, education program targeting parents and children could contribute them reduce potential consequences of children's privacy invasion.

• Knowledge Management Research
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• v.17 no.1
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• pp.17-47
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• 2016

People use social network services (SNSs) for various purposes, for example, to share information, to express themselves, and to strengthen social relationships with others. Meanwhile, problems of personal information leakage and privacy infringement become a social issue and thus information privacy concerns about inappropriate collection and use of personal information increase in SNSs (e.g., Facebook). Although people have privacy concerns in SNSs, they behave in a contradictory way, voluntarily presenting themselves and disclosing personal information. This phenomenon is called 'privacy paradox'. Using dual factor theory, this study investigates the phenomenon of privacy paradox by looking into enablers (e.g., self-presentation) and inhibitors (e.g., information privacy concern) for continuous use of Facebook that can co-exist independently of each other. It also includes antecedents of self-presentation (i.e., narcissism, need for affiliation, involvement, and self-efficacy) and those of information privacy concern (i.e., previous experience of privacy infringement, privacy awareness, and privacy control). The results show that most hypothesized relationships were supported. These findings provide strategic implications for SNS providers who want to promote continuous use of SNS. Under the current circumstances in which enhanced privacy policies are required, this study would be a useful reference for future research on information privacy issues in SNSs.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.89-98
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• 2012

According to the enforcement of Personal Information Protection Act as of September 2011, the laws and regulations for the protection of personal information that were applied only to the certain sectors such as information & communication network, financial institutions, public sector etc. for the time being has been expanded to apply to all public and private sectors to process personal information. In particular, because the public institutions are obliged to be mandatorily conducted of the Privacy Impact Assessment, it will be enforced in earnest for each agency's informationization business that handles personal information. In this paper, I examine the most derived vulnerability and set up the improvement measure to supplement it with the examples of 10 of all the institutions conducting the Privacy Impact Assessment in the year 2011. And, I suggest the measures to be prepared by the institutions to observe the Personal Information Protection Act.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.6
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• pp.197-208
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• 2014

In an information society, privacy protection is one of the most important ethical issues. In medical institutes in which personal medical information is collected and stored, in addition, a privacy breach can cause a serious damage on personal lives. This study attempted to develop privacy concern measurement tool in personal medical information to measure patients' concern on their medical information from medical service consumers' perspective and verify its validity. For this, privacy concern measurement tool in personal medical information was developed based on the results of previous studies. After performing Exploratory Factor Analysis(EFA) and Confirmatory Factor Analysis(CFA) on the measurement tool, its reliability and validity were verified. It appears that the measurement tool would be useful in developing decent privacy protection policy after investigating citizens' concern on the protection of personal medical information and domains they are interested in. For medical institutes as well, they would be helpful in coming up with a reasonable plan after figuring out problems in the protection of personal medical information and current status.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.3
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• pp.558-575
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• 2013

The purpose of a data leakage prevention system is to protect corporate information assets. The system monitors the packet exchanges between internal systems and the Internet, filters packets according to the data security policy defined by each company, or discretionarily deletes important data included in packets in order to prevent leakage of corporate information. However, the problem arises that the system may monitor employees' personal information, thus allowing their privacy to be violated. Therefore, it is necessary to find not only a solution for detecting leakage of significant information, but also a way to minimize the leakage of internal users' personal information. In this paper, we propose two models for representing the level of personal information disclosure during data leakage detection. One model measures only the disclosure frequencies of keywords that are defined as personal data. These frequencies are used to indicate the privacy violation level. The other model represents the context of privacy violation using a private data matrix. Each row of the matrix represents the disclosure counts for personal data keywords in a given time period, and each column represents the disclosure count of a certain keyword during the entire observation interval. Using the suggested matrix model, we can represent an abstracted context of the privacy violation situation. Experiments on the privacy violation situation to demonstrate the usability of the suggested models are also presented.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.788-793
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• 2004

Internet-based distribution of digital contents provides great opportunities for producers, distributors and consumers, but it may seriously threaten users' privacy. The Digital Rights Management (DRM) systems which one of the major issues, concern the protection of the ownership/copyright of digital content. However, the most recent DRM systems do not support the protection of the user's personal information. This paper examines the lack of privacy in DRM systems. We describe a privacy policy and user's privacy preferences model that protect each user's personal information from privacy violation by DRM systems. We allow DRM privacy agent to automatically negotiate between the DRM system policy and user's privacy preferences to be disclosed on behalf of the user. We propose an effective negotiation algorithm for the DRM system. Privacy rules are created following the negotiation process to control access of the user's personal information in the DRM system. The proposed privacy negotiation algorithm can be adapted appropriately to the existing DRM systems to solve the privacy problem effectively.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.43-49
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• 2019

Today, with the development of the internet of things, wearable devices related to personal health care have become widespread. Various global information and communication technology companies are developing various wearable health devices, which can collect personal health information such as heart rate, steps, and calories, using sensors built into the device. However, since individual health data includes sensitive information, the collection of irrelevant health data can lead to personal privacy issue. Therefore, there is a growing need to develop technology for collecting sensitive health data from wearable health devices, while preserving privacy. In recent years, local differential privacy (LDP), which enables sensitive data collection while preserving privacy, has attracted much attention. In this paper, we develop a technology for collecting vast amount of health data from a smartwatch device, which is one of popular wearable health devices, using local difference privacy. Experiment results with real data show that the proposed method is able to effectively collect sensitive health data from smartwatch users, while preserving privacy.