• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.125-139
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• 2013

Big data refers to the data that cannot be processes with conventional contemporary data technologies. As smart devices and social network services produces vast amount of data, big data attracts much attention from researchers. There are strong demands form governments and industries for bib data as it can create new values by drawing business insights from data. Since various new technologies to process big data introduced, academic communities also show much interest to the big data domain. A notable advance related to the big data technology has been in various fields. Big data technology makes it possible to access, collect, and save individual's personal data. These technologies enable the analysis of huge amounts of data with lower cost and less time, which is impossible to achieve with traditional methods. It even detects personal information that people do not want to open. Therefore, people using information technology such as the Internet or online services have some level of privacy concerns, and such feelings can hinder continued use of information systems. For example, SNS offers various benefits, but users are sometimes highly exposed to privacy intrusions because they write too much personal information on it. Even though users post their personal information on the Internet by themselves, the data sometimes is not under control of the users. Once the private data is posed on the Internet, it can be transferred to anywhere by a few clicks, and can be abused to create fake identity. In this way, privacy intrusion happens. This study aims to investigate how perceived personal information overload in SNS affects user's risk perception and information privacy concerns. Also, it examines the relationship between the concerns and user resistance behavior. A survey approach and structural equation modeling method are employed for data collection and analysis. This study contributes meaningful insights for academic researchers and policy makers who are planning to develop guidelines for privacy protection. The study shows that information overload on the social network services can bring the significant increase of users' perceived level of privacy risks. In turn, the perceived privacy risks leads to the increased level of privacy concerns. IF privacy concerns increase, it can affect users to from a negative or resistant attitude toward system use. The resistance attitude may lead users to discontinue the use of social network services. Furthermore, information overload is mediated by perceived risks to affect privacy concerns rather than has direct influence on perceived risk. It implies that resistance to the system use can be diminished by reducing perceived risks of users. Given that users' resistant behavior become salient when they have high privacy concerns, the measures to alleviate users' privacy concerns should be conceived. This study makes academic contribution of integrating traditional information overload theory and user resistance theory to investigate perceived privacy concerns in current IS contexts. There is little big data research which examined the technology with empirical and behavioral approach, as the research topic has just emerged. It also makes practical contributions. Information overload connects to the increased level of perceived privacy risks, and discontinued use of the information system. To keep users from departing the system, organizations should develop a system in which private data is controlled and managed with ease. This study suggests that actions to lower the level of perceived risks and privacy concerns should be taken for information systems continuance.

• Journal of Digital Convergence
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• v.17 no.11
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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.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.441-446
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• 2011

Radio frequency identification (RFID) tags are cheap and simple devices that can store unique identification information and perform simple computation to keep better inventory of packages. Security protocol for RFID tags is needed to ensure privacy and authentication between each tag and their reader. In order to accomplish this, in this paper, we analyzed a lightweight privacy and authentication protocol for passive RFID tags.

• Information Systems Review
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• v.24 no.4
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• pp.55-76
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• 2022

People have adopted Social Networking Sites (SNSs) as a part of their daily lives. When a person uses SNSs, (s)he intentionally or unintentionally discloses her/his personal information. Although using SNSs can provide benefits to a person such as maintaining relationships with people who does not see often, it also opens a dark side. Someone can use one's disclosed information without the acknowledgement of the information owner. It is called a privacy intrusion on SNSs, which has become a social problem and needs attention. This study examined factors affecting privacy intrusion intention on SNSs. This study classifies privacy intrusions into passive intrusion (collector) and active intrusion (distributor). The results reveal that low ethical consciousness positively affects enjoyment in both of collecting and distributing someone's personal information on SNSs. A person who has the low ethical consciousness also tends to raise her/his curiosity of collecting someone's private information on SNSs. Apart from low ethical consciousness, this study discloses how enjoyment, curiosity, experience of being a victim of privacy intrusion, experience of intruding others' privacies, and self-efficacy of collecting or distributing others' private information are related to passive or/and active privacy intrusion on SNSs with survey data.

• Information Systems Review
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• v.16 no.2
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• pp.1-23
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• 2014

With side effects such as Phishing and Spam using personal information in Social Network Service, there is a growing need for studies related to harmful behaviors such as the reason for privacy violation. As such, this study assumed privacy violation to be ethical decision, making behavior and used the Theory of Planned Behavior and Motivation Theory, which are mostly used in social science to identify the factors affecting privacy violation. The results suggested that the Perceived Enjoyment and Punishment used in motivation studies affected privacy violation behaviors, and that the factors of the Theory of Planned Behavior such as Attitude toward Privacy Violation, Subjective Norms of Privacy Violation, and Perceived Behavioral Control with regard to Privacy Violation significantly influenced the Intention to Privacy Violation. On the other hand, Perceived Curiosity and Subjective Norms of Privacy Violation did not affect the Intention to Privacy Violation. Therefore, this study confirmed that the Theory of Planned Behavior was appropriate to explain the Intention to Privacy Violation, and that the variables of the Motivation Theory generally influenced the Attitude toward Privacy Violation. This study was significant since it extended the scope of theoretical privacy study from users and victims centered to inflictor and applied the Extended Theory of Planned Behavior using the variables of the Motivation Theory in the study of Intention to Privacy Violation. From the practical aspect, it provided the ground for privacy education based on the fact that the Attitude toward Privacy Violation can be curbed when education on the Privacy Concerns, Perceived Enjoyment, and Punishment with regard to privacy is strengthened. It also cited the need for the punishment of privacy violation and the practical ground to amend the terms and conditions of user license and Personal Information Protection Act to provide policy support.

• Annual Conference of KIPS
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• 2016.04a
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• pp.461-463
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• 2016

Information security and preservation of customer's data privacy are key factors for further wide spread adoption of microgrid (MG) technology. However, strong coupling between the operation cost of multi-microgrid (MMG) system and privacy of customer data makes it more challenging. A nested energy management system (EMS) has been proposed in this paper. The surplus/shortage information from the inner level MGs is included in processing the optimal operation of outer level MGs. This type of optimization ensures a layered privacy-preservation to customer at each MG level. The proposed EMS architecture is a better trade-off architecture between the operation cost of the MMG system and customer privacy-preservation at each level of MG.

• Journal of Korea Multimedia Society
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• v.12 no.12
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• pp.1796-1808
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• 2009

Elementary school students have a little awareness of privacy protection since they do not have many opportunities for systematic education on information and communication ethics. Hence, they are likely to expose their own information to others and sometimes bring on a lot of misuses by using others' information. In this paper, we provide an idea for teaching and learning methods which the elementary school students acquire privacy protection and management methods and raise their practical capabilities. We develop a role play teaching and learning model in connection with various Information and Communication Technology (ICT) activities and establish the instruction plans. Moreover, we apply them to the actual classes at grade five and six of the elementary school students respectively, and finally analyze the results. The proposed teaching and learning method shows that the students participated in a series of learning activities have higher learning effects on awareness of privacy protection than those learned with the conventional methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.2
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• pp.305-312
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• 2020

The Privacy Act stipulates that the privacy policy document, which is a privacy statement, should be disclosed in order to guarantee the rights of the information subjects, and the Fair Trade Commission considers the privacy policy as a condition and conducts an unfair review of the terms and conditions under the Terms and Conditions Control Act. However, the information subjects tend not to read personal information because it is complicated and difficult to understand. Simple and legible information processing policies will increase the probability of participating in online transactions, contributing to the increase in corporate sales and resolving the problem of information asymmetry between operators and information entities. In this study, complex personal information processing policies are analyzed using deep learning, and models are presented for acquiring simplified personal information processing policies that are highly readable by the information subjects. To present the model, the personal information processing policies of 258 domestic companies were established as data sets and analyzed using deep learning technology.

• Journal of Digital Convergence
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• v.15 no.12
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• pp.265-272
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• 2017

As Location-based services on smartphone are getting more popular, users have more concern on exposing their location information. This study developed a research model to identify how smartphone users perceive on providing information pertaining to their location based on privacy calculus theory. 203 responses were analyzed with SmartPLS 2.0. The outcome of this research is quite interesting because conventional belief of privacy calculus perspective does not hold. The privacy calculus theory is based on assumption that human being is rational and decision to provide privacy information is determined by risk and benefit aspects. However, the result of this study is in accordance with behavioral economics perspective in which emotional judgment and behavioral judgement are affected by different factors.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.1
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• pp.33-43
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• 2013

The research on data mining that can manage a large amount of information efficiently has grown with the drastic increment of information. Privacy-preserving data mining can protect the privacy of data owners. There are several privacy-preserving association rule, clustering and classification protocols. A privacy-preserving association rule protocol is used to find association rules among data, which is often used for marketing. In this paper, we propose a privacy-preserving k-bits inner product protocol based on Shamir's secret sharing.