• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1049-1056
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• 2010

Recently RFID system has been adopted in various fields rapidly. However, we should 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 these problems, There is the 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 creasing numbers of Tag. Therefore We, suggest SP-Division algorithm satisfied with all necessary security of Privacy Protection Scheme and decreased in Tag Identification Time in this paper. And this paper implemented it in time standard finding the first key among the data devided into each nodes. The length of Hash-Chain holds 1000, and the total number of SPs increases 1000, 2000, 3000, and 4000. Comparing tag identification time by the total number of SPs and the number of Nodes with single node, extending the number of nodes to 1, 2, 3 and 4, when the number of nodes is 2, 40% of Performance, when the number of nodes is 3, 56%, and when the number of nodes is 4, 71% is improved.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.5
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• pp.797-802
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• 2011

RFID is recognized to technically occupy important position in ubiquitous computing environment and expected to create new markets in a variety of fields from now on. In order to generalize RFID system, it is required to solve the problem of privacy invasion and expedite lots of tags We suggest efficient RFID Tag Identification to identify tags quickly on the satisfaction with 3 security requirements of privacy protection in this paper. This methods are transferred to Grid environment through parallel analysis of Hash-Chain, and we measure performance of each nodes under the Grid environment. Then, We'll suggest SP-Division Algorithm to identify tags with each nodes and implement it in a Grid environment.

• Review of KIISC
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• v.18 no.5
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• pp.125-131
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• 2008

유비쿼터스 홈네트워크에서는 다양한 디바이스를 이용하여 복수의 도메인을 오가며 서비스를 제공하거나 제공받을 수 있을 것으로 기대되는데 이때 디바이스는 반드시 정당한 디바이스여야 하며 이를 실현하기 위하여 인증서를 사용하는 디바이스 인증 기술이 제안되었다. 그리고, 계산 능력이 작은 디바이스를 인증하기 위한 방법으로서 대칭키 암호 기술에 기반을 둔 디바이스 인가 방법을 함께 사용함으로써 계산 능력이 다른 다양한 디바이스들을 인증하는 방법이 제안되었다. 이들 방법의 공통성은 사용자의 개인 정보 유출을 피하기 위하여 사용자 정보를 사용하지 않고 디바이스 고유의 정보만을 사용하여 인증한다는데 있다. 이러한 디바이스 인증/인가 방법을 홈네트워크에 사용하였을 경우 사용자의 개인 정보는 보호되는지 확인할 필요가 있다. 본 논문에서는 기존에 제안된 유비궈터스 홈네트워크를 위한 디바이스 인증/인가 기술을 분석하여 개인 정보의 유출에 관한 문제점을 도출하고 그에 대한 대응 방법을 제안하였다.

• The KIPS Transactions:PartC
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• v.15C no.3
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• pp.167-172
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• 2008

Fingerprinting scheme supports the copyright protection to track redistributors of digital content using cryptographic techniques. Fingerprinting schemes should guarantee buyer's anonymity and asymmetry for their privacy. Most of known fingerprinting schemes adopt public-key cryptosystems to achieve asymmetry and discrete logarithm problem or graph isomorphism problem to achieve anonymity. However, these schemes are not suited in mobile environment because of the drawbacks of requiring high computational complexity. In this paper, we propose an efficient fingerprinting scheme for mobile environment to provide not only asymmetry of the protocol but also transaction anonymity of the buyer. By employing symmetric encryption to encrypt the digital content and adopting agent to perform the protocols, the efficiency of the proposed scheme is improved.

• Convergence Security Journal
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• v.13 no.4
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• pp.47-52
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• 2013

VANET(Vehicular Ad-hoc Network) is a kind of ad hoc networks which is consist of intelligence vehicular ad nodes, and has become a hot emerging research project in many fields. It provides traffic safety, cooperative driving and etc. but has also some security problems that can be occurred in general ad hoc networks. In VANET, it has been studies that group signature method for user privacy. However, among a group of group key generation phase and group key update phase, RSU(Road-Side Unit) and the computational overhead of the vehicle occur. In this paper, we propose an efficient group key management techniques with CBF(Counting Bloom Filter). Our group key management method is reduced to the computational overhead of RSU and vehicles at the group key generation and renewal stage. In addition, our method is a technique to update group key itself.

• Journal of Korea Spatial Information System Society
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• v.11 no.3
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• pp.19-30
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• 2009

Recent development in wireless communication technology and mobile equipment like PDA, cellular phone and GPS makes location-based services (LBSs) popular. However, because, in the LBSs, users continuously request a query to LBS servers by using their exact locations, privacy information could be in danger. Therefore, a mechanism for users' privacy protection is required for the safe and comfortable use of LBSs by mobile users. For this, this paper propose a grid-based cloaking area creation scheme supporting continuous LBSs. The proposed scheme creates a cloaking area rapidly by using grid-based cell expansion to efficiently support the continuous LBSs. In addition, to generate a cloaking area which makes the exposure probability of a mobile user to a minimum, we compute a privacy protection degree by granting weights to mobile users. Finally, we show from a performance analysis that our cloaking scheme outperforms the existing cloaking schemes, in terms of service time, privacy protection degree.

• 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.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1401-1414
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• 2018

The k-means clustering algorithm groups input data with the number of groups represented by variable k. In fact, this algorithm is particularly useful in market segmentation and medical research, suggesting its wide applicability. In this paper, we propose a privacy-preserving clustering algorithm that is appropriate for outsourced encrypted data, while exposing no information about the input data itself. Notably, our proposed model facilitates encryption of all data, which is a large advantage over existing privacy-preserving clustering algorithms which rely on multi-party computation over plaintext data stored on several servers. Our approach compares homomorphically encrypted ciphertexts to measure the distance between input data. Finally, we theoretically prove that our scheme guarantees the security of input data during computation, and also evaluate our communication and computation complexity in detail.