• Journal of the Korea Society of Computer and Information
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• v.27 no.1
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• pp.193-200
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• 2022

In this paper, we examined the causes of privacy concerns and related factors in social log-in services. On the basis of the 'principal-agent theory,' we established factors such as perceived information asymmetry and fear of seller opportunism affecting information privacy concern of social log-in services users. In addition, we analyzed the relationship between the information privacy concern and intention to use on the basis of the 'privacy calculus theory'. The results of the study showed that (1) fear of seller opportunism had the significant effect on information privacy concerns, (2) information privacy concerns had the significant effect on perceived risk, (3) in accordance with the privacy calculus theory, perceived risk had the negative effect on intention to use, while perceived benefit had the positive effect on intention to use. The findings of the study are expected to help to improve the social log-in service firms' understanding for customers' information privacy protection behaviors.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.254-266
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• 2020

The purpose of this study is to analyze the influence of the type of recommender system on consumer's perceived benefit and privacy risk. The result showed that the perceived usefulness and intension to click was high in the order of Hybrid-filtering, Bestseller, and SNS-based system. Privacy concern was high in order of SNS-based system, Hybrid-filtering, and Bestseller. Moderating effects of perceived personalization on the type of recommender system and perceived usefulness were significant. Finally perceived usefulness had positive effect, and privacy concern had negative effect on consumer's intension to click. This study has significant implications for digital marketing bt comparing consumer responses according to the type of recommended service. The result of this study can be helpful for providing and developing future recommender service.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.245-248
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• 2008

최근 RFID 시스템의 채택이 다양한 분야에서 빠르게 진행되고 있다. 그러나 RFID 시스템의 대중화를 위해서는 RFID 태그의 정보를 무단으로 획득함으로써 발생할 수 있는 프라이버시 침해 문제를 해결해야 한다. 이 문제를 해결하기 위해서 기존 연구들 중에서 가장 안전한 M. Ohkubo 등의 Hash-Chain 기법이 있다. 그러나 이 기법은 태그를 판별할 때 엄청난 태그 수의 증가로 인해 막대한 계산 능력을 요구하는 문제점이 있다. 따라서 본 논문에서는 프라이버시 보호를 유지하면서 태그판별시간 절감을 위해서 그리드 환경으로의 이식과 노드별로 m/k개의 SP를 분할하는 균등분할 알고리즘을 적용한 태그 판별 처리 모델을 제안한다. 제안 모델을 그리드 환경에서 동시에 수행할 수 있다면 이상적인 경우 태그를 판별하는 시간은 1/k로 감소한다.

• Knowledge Management Research
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• v.22 no.2
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• pp.33-53
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• 2021

Use of mobile apps being extended, privacy concern on the side of the users is increased while they are willing to provide the private information to use the apps. In this study, we tried to identify the motivating elements that influence the users' intention to use the apps, based on the tendency towards regulatory focus and the privacy calculus theory. To verify the study model, we collected data from 151 adults who use health apps throughout the country, and analyzed the data using the PLS-SEM method. According to the result of the study, it was turned out that tendency towards promotion focus had negative impact on privacy concern and privacy danger, and tendency towards prevention focus had positive impact on privacy concern. Privacy concern had negative impact on the intention to use the mobile apps, and privacy benefit and privacy knowledge had positive impact on the intention to use the mobile apps. Finally, the intention to use the mobile apps had positive impact on the intention to continue to use the mobile apps. In this study, we identified different impacts of two types of tendency towards regulatory focus on privacy concern, and identified different influences on the intention to use the mobile apps accordingly.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.797-799
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• 2013

오늘날 슈퍼컴퓨팅은 급격히 진화하고 있다. 본 연구는 이러한 고성능 슈퍼컴퓨터의 다양한 과학적 융합 서비스와 관련한 가시화의 중요성을 인식하고, 이와 관련하여 융합 서비스에서의 소비자 프라이버시 침해 우려에 대한 문제를 제기한다. 이를 위하여, 슈퍼컴퓨팅 및 소비자 프라이버시에 대한 문헌연구를 하였고, 프라이버시 계산 모델을 이용한 연구의 필요성과 소비자들로 하여금 프라이버시 정책에 대한 인식의 중요성, 금전적 보상에 따른 개인정보의 긍정적 제공이라는 3 가지의 방안을 제언하였다.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.4
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• pp.7-17
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• 2019

Machine learning is one of the most accurate techniques to predict and analyze various phenomena. K-means clustering is a kind of machine learning technique that classifies given data into clusters of similar data. Because it is desirable to perform an analysis based on a lot of data for better performance, K-means clustering can be performed in a model with a server that calculates the centroids of the clusters, and a number of clients that provide data to server. However, this model has the problem that if the clients' data are associated with private information, the server can infringe clients' privacy. In this paper, to solve this problem in a model with a number of clients, we propose a privacy-preserving K-means clustering method that can perform machine learning, concealing private information using homomorphic encryption.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.1
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• pp.81-87
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• 2009

Recently RFID system has been adopted in various fields rapidly. However, we ought to solve the problem of privacy invasion that can be occurred by obtaining information of RFID Tag without any permission for popularization of RFID system To solve the problems, it is Ohkubo et al.'s Hash-Chain Scheme which is the safest method. However, this method has a problem that requesting lots of computing process because of increasing numbers of Tag. Therefore, in this paper we apply the previous method into the grid environment by analyzing Hash-Chain scheme in order to reduce processing time when Tags are identified. We'll implement the process by offering Tag Identification Process Model to divide SPs evenly by node.

• Journal of Convergence for Information Technology
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• v.8 no.5
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• pp.107-113
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• 2018

With the rapid development of big data and Internet technologies among IT technologies, it is being changed into an environment where data stored in the cloud environment can be used wherever the Internet is connected, without storing important data in an external storage device such as USB. However, protection of users' privacy information is becoming increasingly important as the data being processed in the cloud environment is changed into an environment that can be easily handled. In this paper, we propose a user-reserving management model that can improve the user 's service quality without exposing the information used in the cloud environment to a third party. In the proposed model, user group is grouped into virtual environment so that third party can not handle user's privacy information among data processed in various cloud environments, and then identity property and access control policy are processed by block chain.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.6
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• pp.1010-1015
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• 2008

The choice of RFID system is recently progressing(being) rapidly at various field. For the sake of RFID system popularization, However, We should solve privacy invasion to gain the pirated information of RFID tag. There is the safest M Ohkubos's skill among preexistent studying to solve these problems. But, this skill has a problem that demands a immense calculation capability caused an increase in tag number when we discriminate tags. So, This paper proposes the way of transplant to Grid environment for keeping Privacy Protection up and reducing the Tag Identification Time. And, We propose the Tag Identification Process Model to apply Even Division Algorithm to separate SP with same site in each node. If the proposed model works in Grid environment at once, it would reduce the time to identify tags to 1/k.

• Journal of Digital Contents Society
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• v.18 no.5
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• pp.957-967
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• 2017

In this study, factor, is focused on user's psychology and SNS using style, of intention to use SNS continuously being affeted to who want to stop using SNS. This study utilized the foundational frame of PCM and TAM2 and indepednent variable and Mediating variable were based on previous research. I used statistical programs such as AMOS 18.0 and SPSS 18.0 to verify the practical examination of the hypothesis of this study and the questionnaire was distributed to the public and IT students who once used SNS, and made the 443 questionnaires to analyze on final except missing values and insincere responses. The result of study was that intention to use SNS continuously are affected by positive and negative psychological factors and will be helpful to provide a service plan for SNS and establish for marketing strategy.