• The KIPS Transactions:PartC
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• v.14C no.5
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• pp.439-452
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• 2007

We study on the privacy preserving data mining, PPDM for short, by using randomization. The theoretical PPDM based on the secure multi-party computation techniques is not practical for its computational inefficiency. So we concentrate on a practical PPDM, especially randomization technique. We survey various privacy measures and study on the privacy preserving mining of association rules by using randomization. We propose a new randomization operator, binomial selector, for privacy preserving technique of association rule mining. A binomial selector is a special case of a select-a-size operator by Evfimievski et al.[3]. Moreover we present some simulation results of detecting an appropriate parameter for a binomial selector. The randomization by a so-called cut-and-paste method in [3] is not efficient and has high variances on recovered support values for large item-sets. Our randomization by a binomial selector make up for this defects of cut-and-paste method.

• The KIPS Transactions:PartC
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• v.16C no.5
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• pp.563-574
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• 2009

The merits of random substitutions are various applicability and security guarantee on the view point of privacy breach. However there is no research to improve the accuracy of random substitutions. In this paper we propose an algorithm for improving the accuracy of random substitutions by an advanced theoretical analysis about the standard errors. We examine that random substitutions have an unpractical accuracy level and our improved algorithm meets the theoretical results by some experiments for data sets having uniform and normal distributions. By our proposed algorithm, it is possible to upgrade the accuracy level under the same security level as the original method. The additional cost of computation for our algorithm is still acceptable and practical.

• Information Systems Review
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• v.15 no.1
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• pp.105-122
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• 2013

Given the proliferation of social network services, it has become important to understand its user's continued use behavior. As users' privacy concerns in SNS have been identified as a critical barrier against forming this continued intention, many studies have focused on inducing continued intention by mitigating privacy concerns. However, this paper suggests to approach users' continued intention not only from the perspective of mitigating privacy concerns but also from the perspective of increasing potential benefits. Under the theoretical framework of privacy calculus model, we conducted cross sectional survey on 150 Facebook and 150 KakaoTalk users. The result suggests that trust mediates the relationships between privacy concerns and continued intention and between network externality and continued intention, and the influence of support for network formation on continued intention. The effect of network externality on continued intention, however, is not significant among Facebook users while it is significant among KakaoTalk users.

• Knowledge Management Research
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• v.25 no.2
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• pp.219-243
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• 2024

This study investigates the impact of privacy concerns, perceived utility, and awareness of the right to personal data self-determination on the effective use and expansion of MyData services, which are critical to the data economy. Integrating the value-based adoption model with privacy calculus theory, the research examines how perceived utility, privacy concerns, trust, and personal innovativeness influence perceived value, perceived privacy, and the intention to provide personal information. Data collected from an online survey of 442 MyData service users and prospective users were analyzed using PLS-SEM and Bootstrapping methods via SmartPLS 4. The results indicate that perceived utility positively affects the intention to provide personal information, while privacy concerns have a negative impact. Trust and personal innovativeness positively influence the intention to adopt MyData services, and the awareness of personal data self-determination rights moderates these intentions. The findings underscore the importance of developing beneficial services that mitigate users' privacy concerns and build trust for the successful implementation of MyData services. Additionally, the study highlights the need for education and awareness campaigns to enhance understanding of the right to personal data self-determination.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.5
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• pp.299-306
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• 2002

Partially blind signature scheme is used in applications such as electronic cash and electronic voting where the privacy of the signature requester is important. This paper proposes an RSA-based enhanced partially blind signature scheme minimizing the amount of computation of the signature requester. The signature requester needs computation in blinding the message to the signer and in generating the final signature using the intermediate signature generated by the signer. Since the proposed scheme enables the signature requester to get the final signature just by using modular additions and multiplications, it decreases computation of the signature requester considerably. So, the proposed partially blind signature scheme is adequate for devices such as mobile device, smart-card, and electronic purse that have relatively low computing power.

• 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.

• 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.

• The KIPS Transactions:PartC
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• v.18C no.5
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• pp.331-338
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• 2011

The RFID system includes a section of wireless communication between the readers and the tags. Because of its vulnerability in terms of security, this part is always targeted by attackers and causes various security problems including the leakage of secret and the invasion of privacy. In response to these problems, various protocols have been proposed, but because many of them have been hardly implementable they have been limited to theoretical description and theorem proving without the accurate verification of their safety. Thus, this study tested whether the protocol proposed by Kenji et al. satisfies security requirements, and identified its vulnerabilities such as the exposure of IDs and messages. In addition, we proposed an improved RFID security protocol that reduced the number of public keys and random numbers. As one of its main characteristics, the proposed protocol was designed to avoid unnecessary calculations and to remove vulnerabilities in terms of security. In order to develop and verify a safe protocol, we tested the protocol using Casper and FDR(Failure Divergence Refinements) and confirmed that the proposed protocol is safe in terms of security. Furthermore, the academic contributions of this study are summarized as follows. First, this study tested the safety of a security protocol through model checking, going beyond theorem proving. Second, this study suggested a more effective method for protocol development through verification using FDR.

• Information Systems Review
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• v.17 no.2
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• pp.77-100
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• 2015

This study examined the factors that influence the smartphone user's decision to accept the personalized mobile advertisement. As a theoretical basis, we applied the privacy calculus model (PCM) that illustrates how consumers are engaged in a dynamic adjustment process in which privacy risks are weighted against benefits of information disclosure. In particular, we investigated how smartphone users make a risk-benefit assessment under which personalized service as benefit-side factor and information privacy risks as a risk-side factor accompanying their acceptance of advertisements. Further, we extend the current PCM by considering advertisement fatigue as a new factor that may influence the user's acceptance. The research model with five (5) hypotheses was tested using data gathered from 215 respondents through a quasi-experimental survey method. During the survey, each participant was asked to navigate the website where the experimental simulation of a mobile advertisement service was provided. The results showed that three (3) out of five (5) hypotheses were supported. First, we found that the intention to accept advertisements is positively and significantly influenced by the perceived value of personalization. Second, perceived advertisement fatigue was also found to be a strong predictor of the intention to accept advertisements. However, we did not find any evidence of direct influence of privacy risks. Finally, we found that the significant moderating effect between the perceived value of personalization and advertisement fatigue. This suggests that the firms should provide effective tailored advertisement that can increase the perceived value of personalization to mitigate the negative impacts of advertisement fatigue.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.283-311
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• 2024

This study examined the factors affecting the intention of the public to share electronic medical records(EMR) based on the theory of reasoned action and the privacy calculus model. It also investigated whether the purpose of EMR sharing varies depending on personal characteristics, such as the degree of interest in health and personal medical history. According to an online survey of 145 people, altruistic enjoyment, awareness of personal information protection, recognition of legal and institutional roles, and interest in health had a positive impact on the level of EMR sharing, and trust in hospitals positively adjusted the relationship between recognition of legal and institutional roles and sharing intentions. Accordingly, we confirmed that the public recognized the role of the government and hospitals in the sharing process as necessary. The public interest benefits of sharing are critical to activating public participation in the sharing of EMR, and it is also essential to prepare guidelines that legally guarantee the security and proper use of EMR.