• Journal of Digital Convergence
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• v.17 no.11
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• pp.149-156
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• 2019

With widespread use of information technologies, information privacy issues have been gaining more attention by not only the public but also researchers. The number of studies on the issues has been increasing exponentially, which makes incomprehensible the whole picture of research outcome. Thus, it is necessary to conduct a systematic examination of past research. This study developed two competing models with four essential constructs in information privacy research and empirically tested the models with data obtained from previous studies. This study employed a quantitative meta-analysis method called TSSEM. It is one of MASEM methods in which structural equation modeling and meta-analysis are integrated. The analysis results indicated that risk-centric model exhibited much better model fits than those of concern-centric model. This study implies that traditional concern-centric model should be questioned it's explanatory power of the model and researchers may consider alternative risk-centric model to explain user's intention to provide privacy information.

• Information Systems Review
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• v.25 no.3
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• pp.99-120
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• 2023

Courier services users' experience of violating privacy affects psychology and behavior of protecting personal privacy. Depending on what privacy infringement experience (PIE) of courier services users, learning about perceived privacy infringement incidents is made, recognition is formed, affection is formed, and behavior is appeared. This paradigm of changing in privacy psychologies of courier services users has an important impact on predicting responses of privacy protective action (PPA). In this study, a theoretical research framework are developed to explain the privacy protective action (PPA) of courier services users by applying attitude theory. Based on this framework, the relationships among past privacy infringement experience (PIE), perceived privacy risk (PPR), privacy concerns (i.e., concerns in unlicensed secondary use (CIUSU), concerns in information error (CIE), concerns in improper access (CIA), and concern in information collection (CIC), and privacy protective action (PPA) are analyzed. In this study, the proposed research model was surveyed by people with experience in using courier services and was analyzed for finding relationships among research variables using structured an equation modeling software, SMART-PLS. The empirical results show the causal relationships among PIE, PPR, privacy concerns (CIUSU, CIE, CIA, and CIC), and PPA. The results of this study provide useful theoretical implications for privacy management research in courier services, and practical implications for the development of courier services business model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1717-1732
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• 2015

The widespread use of location-based services (LBSs), which allows untrusted service provider to collect large number of user request records, leads to serious privacy concerns. In response to these issues, a number of LBS privacy protection mechanisms (LPPMs) have been recently proposed. However, the evaluation of these LPPMs usually disregards the background knowledge that the adversary may possess about users' contextual information, which runs the risk of wrongly evaluating users' query privacy. In this paper, we address these issues by proposing a generic formal quantification framework,which comprehensively contemplate the various elements that influence the query privacy of users and explicitly states the knowledge that an adversary might have in the context of query privacy. Moreover, a way to model the adversary's attack on query privacy is proposed, which allows us to show the insufficiency of the existing query privacy metrics, e.g., k-anonymity. Thus we propose two new metrics: entropy anonymity and mutual information anonymity. Lastly, we run a set of experiments on datasets generated by network based generator of moving objects proposed by Thomas Brinkhoff. The results show the effectiveness and efficient of our framework to measure the LPPM.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.4
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• pp.213-225
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• 2019

Privacy paradox is a paradoxical behavior that provides personal information even though you are concerned about privacy. Social media users are also often concerned about their personal information exposure. It is even reluctant to describe personal information in profile. However, some users describe their personal information in detail on their profile, provide it freely when others request it, or post their own personal information. The survey was conducted using Google Docs centered on Facebook users. Structural equation model analysis was used for hypothesis testing. As an independent variable, we use personal information infringement experiences. As a mediator, we use privacy indifference, privacy concern, and the relationship with the act of providing personal information. Social media users have become increasingly aware of the fact that they can not distinguish between the real world and online world by strengthening their image and enhancing their image in the process of strengthening ties, sharing lots of information and enjoying themselves through various relationships. Therefore, despite the high degree of privacy indifference and high degree of privacy concern, the phenomenon of privacy paradox is also present in social media.

• Journal of Digital Convergence
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• v.11 no.1
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• pp.237-242
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• 2013

SNS is emerging as an academic and social interest, as Facebook and Twitter are developed explosively. But, SNS has a problem of exposing user's privacy because it is originated by exchanging user's personal information and opinion. This paper proposes SNS user privacy protecting model using data separation and false data information instead of blocking which is using to protect user's personal privacy. The proposed model do not let the third party extract precise information after collecting user's context information by adding false information to separated context information. Also, it gets user's agreement beforehand if SNS service provider uses user's information not to be used illegally by the third party.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3419-3437
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• 2022

Anonymization technology is an important technology for privacy protection in the process of data release. Usually, before publishing data, the data publisher needs to use anonymization technology to anonymize the original data, and then publish the anonymized data. However, for data publishers who do not have or have less anonymized technical knowledge background, how to configure appropriate parameters for data with different characteristics has become a more difficult problem. In response to this problem, this paper adds a historical configuration scheme resource pool on the basis of the traditional anonymization process, and configuration parameters can be automatically recommended through the historical configuration scheme resource pool. On this basis, a privacy model hybrid recommendation algorithm for user satisfaction is formed. The algorithm includes a forward recommendation process and a reverse recommendation process, which can respectively perform data anonymization processing for users with different anonymization technical knowledge backgrounds. The privacy model hybrid recommendation algorithm for user satisfaction described in this paper is suitable for a wider population, providing a simpler, more efficient and automated solution for data anonymization, reducing data processing time and improving the quality of anonymized data, which enhances data protection capabilities.

• Information Systems Review
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• v.16 no.3
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• pp.191-214
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• 2014

In this study, based on Privacy Calculus Model, we study whether users' intention of continuous use of closed-type SNS is affected by information privacy concern. In addition, we propose a model that studies if the major factors of the intention of continuous use which are trust, satisfaction and benefits could control the information privacy concern's effect on the intention of use. As a result, companies have to consider protecting the psychological privacy and information privacy of the individual when they design SNS.

• The Journal of Information Systems
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• v.23 no.4
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• pp.119-145
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• 2014

Under the premise that information privacy concerns can atrophy e-commerce by causing particular behaviors of Internet users, this study focused on exploring the causes of information privacy concerns, the related information privacy protective responses of Internet users, and measures for alleviating the information privacy concerns. This study is based on the 'principal-agent theory,' and established the following as factors that cause information privacy concerns of Internet users: perceived information non-transparency; perceived action uncertainty. Also, the information privacy concerns caused by the factors were established as the cause of information privacy protective responses of Internet users. Also, the concept of 'signaling' and 'incentive,' which were presented to solve the adverse selection and moral hazard issue in the host-agent theory, was introduced to establish the following as factors that alleviate information privacy concerns: trust; informativeness. Those factors were included in the research model to conduct an empirical analysis. The analysis has revealed that both the perceived information non-transparency (p<0.01) and perceived action uncertainty (p<0.01) as to websites had a significant impact on information privacy concerns. Also, information privacy concerns of Internet users (p<0.01) had a significant impact on their information privacy protective responses who strive to protect their personal information. In addition, when trust and informativeness, which were established as factors that can alleviate information privacy concerns, were empirically analyzed, trust and informativeness had the effect of alleviating information privacy concerns. Based on the findings, the following was confirmed: Boosting the trust of Internet users in websites and offering useful information related to personal data can play a key role in alleviating the information privacy concerns of Internet users.

• Information Systems Review
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• v.22 no.2
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• pp.101-120
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• 2020

This study investigates the effects of privacy psychological characteristics of B2C logistics services users on their willingness to comply with their logistics companies' information protection policy. Using cognitive valence theory as a theoretical framework, this study proposes a research model to examine the relationships between users' logistics security knowledge, privacy trust, privacy risk, privacy concern, and their willingness of information protection policy compliance. To test the proposed model, we conducted a survey from actual users of logistics services and collected valid 151 samples. We analyzed the data using a structural equation modeling software. The empirical results show that logistics security knowledge positively affects privacy trust; privacy concern positively influences privacy risk; privacy trust, privacy risk, and privacy concern positively influence behavioral willingness of compliance. However, logistics security knowledge does not affect behavioral willingness of compliance. The results of the study provide several contributions to the literature of B2C logistics services domain and managerial implications to logistics services companies.

• Journal of Computing Science and Engineering
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• v.7 no.3
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• pp.177-186
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• 2013

We briefly review the problem of statistical disclosure control under differential privacy model, which entails a formal and ad omnia privacy guarantee separating the utility of the database and the risk due to individual participation. It has born fruitful results over the past ten years, both in theoretical connections to other fields and in practical applications to real-life datasets. Promises of differential privacy help to relieve concerns of privacy loss, which hinder the release of community-valuable data. This paper covers main ideas behind differential privacy, its interactive versus non-interactive settings, perturbation mechanisms, and typical applications found in recent research.