• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.3
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• pp.159-177
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• 2015

As smart phones become more common nowadays, mobile instant messengers such as kakao talk and line are used as essential communication tools exchanging information between individuals. Also, the mobile instant messengers extend their use to business area beyond communication between individuals. This study is on how factors of mobile instant messenger such as perceived security, perceived privacy, perceived enjoyment and perceived interactivity affect business continual usage intention through perceived usefulness. The proposed model is based on Expectation-Confirmation Theory of Oliver and Technology Acceptance Mode of Bhattacherjee. For an analysis, 159 survey responses were collected from the office workers in Seoul and nearby cities, having experiences of mobile instant messengers. To validate the proposed research model, PLS analysis is performed with the valid 154 questionnaires. The path analysis results are as follows. First, perceived security has a positive effect on expectation-confirmation. Second, perceived enjoyment has a positive effect on perceived usefulness. Third, perceived interactivity has a positive effect on both perceived usefulness and expectation-confirmation. Fourth, perceived usefulness has a positive usefulness on satisfaction and continual usage intention of mobile instant messenger. Last, expectation-confirmation has a positive effect on perceived usefulness, and satisfaction has a positive effect on continual usage intention of mobile instant messenger. Since the mobile instant messenger may bring a pressure of work and a violation of privacy, it is necessary that the company provide a guideline for use of the mobile instant messenger and establish the in-house mobile instant messenger system.

• Asia pacific journal of information systems
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• v.16 no.4
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• pp.49-70
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• 2006

In recent, Open markets are booming up rapidly. Open markets are one of the online marketplaces which mainly concentrated on spot transactions of commodities, and are differentiated from integrated internet shopping stores with market participants, trading rules and so on. This study investigated on factors affecting satisfaction with and preference on open markets by comparing open markets with integrated internet shopping stores, and aimed to figure out the reasons why open markets are growing up so rapidly and to forecast the future of open markets. To investigate the factors affecting buyers' satisfaction with and preference on internet shopping channel. I extracted several factors through literature reviews. The factors include the pros (cost saving and time saving), the cons (security concerns and privacy concerns), and decision making support suggested by Simon's research as well. Then, I constructed research model and related research hypotheses. To verify research hypotheses, I conducted field survey targeting on online buyers and analyzed research data using structural equation model. According to data analysis result, open markets have competitive advantages over integrated internet shopping stores with respect to cost saving, time saving, and decision making support. However, online buyers are still concerning privacy issues within open markets. In summary, buyers are considering that open markets are cheaper, faster, and more efficient internet shopping channel, compared with integrated internet shopping stores. However, open markets are required to dedicate to lessen buyers' privacy concerns to rebirth as more satisfying and preferable internet shopping channel and to prosper in the future.

• Journal of Digital Contents Society
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• v.9 no.4
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• pp.697-705
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• 2008

The recent web technology has been developed by three mainsprings which include integration, virtualization, and socialization. The web technology provides the increment of the social networking ability. However it deepens the exposure of privacy about personal information as more complicating and difficult problems. Representatively, it is impossible to define and manage the specific relation, so the personal information and interest can be inferred from collecting and summarizing the contents. Also, there are some problems that it is hard to construct the information owner's own social network. Thus this paper proposes the RCBAC(Relationship-Content based Access Control) Model which applies both the concepts of Relationship and Content Semantic to the existing access control methods to protect the user's own digital contents in web 2.0 environment. This method prevents privacy such as personal inclination from being exposed and enables to define and manage the specific relation. By doing this the information owners can construct their social network. This social network can be applied and extended to web contents.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.549-552
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• 2013

The research conducted here focuses on the definition and organization of information privacy concerns in e-commerce process. Based on the identified concept of information privacy concerns(IPC), this study additionally explores the interrelationships among consumers' individual characteristics(self-efficacy, digital literacy, customer alienation), customer satisfaction and intention to buy. Through empirical model analysis, this study found that self-efficacy and digital literacy affect negatively IPC, while customer alienation has an positive effect on IPC. IPC affects positively customer satisfaction. Academically, this study extends IPC to an empirical research model by identifying the conceptualization and organization of IPC. Moreover, practically, e-commerce providers can develop how to relieve IPC of online consumers.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.4
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• pp.111-122
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• 2008

Web service is defined to support interoperable machine to machine interaction over a network and defined as distributed technologies. Recently in web service environment, security has become one of the most critical issues. An attacker may expose user privacy and service information without authentication. Furthermore, the users of web services must temporarily delegate some or all of their behalf. This results in the exposure of user privacy information by agents. We propose a delegation model for providing safety of web service and user privacy in ubiquitous computing environments. In order to provide safety of web service and user privacy, XML-based encryption and a digital signature mechanism need to be efficiently integrated. In this paper, we propose web service management server based on XACML, in order to manage services and policies of web service providers. For this purpose, we extend SAML to declare delegation assertions transferred to web service providers by delegation among agents.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.2
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• pp.73-90
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• 2010

Recently, Tan et al. introduced a serverless search protocol in which a mobile reader maintains a tag authentication list and authenticates a tag using the list without connecting authentication server. A serverless RFID system is different from general RFID systems which use on-line server models. In the serverless RFID system, since the mobility of a personalized reader must be considered, we have to protect not only the privacy of a tag but also the privacy of a mobile reader. In this paper, we define new security requirements for serverless RFID search system and propose a secure serverless RFID search system. In our system, since tag authentication information maintained by a reader is updated in every session, we can provide the backward untraceability of a mobile reader. Also we use an encrypted timestamp to block a replay attack which is major weakness of search protocols. In addition, we define a new adversary model to analyze a serverless RFID search system and prove the security of our proposed system using the model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.958-979
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• 2023

Due to laws, regulations, privacy, etc., between 70-90 percent of providers do not share medical data, forming a "data island". It is essential to collaborate across multiple institutions without sharing patient data. Most existing methods adopt distributed learning and centralized federal architecture to solve this problem, but there are problems of resource heterogeneity and data heterogeneity in the practical application process. This paper proposes a collaborative deep learning modelling method based on the blockchain network. The training process uses encryption parameters to replace the original remote source data transmission to protect privacy. Hyperledger Fabric blockchain is adopted to realize that the parties are not restricted by the third-party authoritative verification end. To a certain extent, the distrust and single point of failure caused by the centralized system are avoided. The aggregation algorithm uses the FedProx algorithm to solve the problem of device heterogeneity and data heterogeneity. The experiments show that the maximum improvement of segmentation accuracy in the collaborative training mode proposed in this paper is 11.179% compared to local training. In the sequential training mode, the average accuracy improvement is greater than 7%. In the parallel training mode, the average accuracy improvement is greater than 8%. The experimental results show that the model proposed in this paper can solve the current problem of centralized modelling of multicenter data. In particular, it provides ideas to solve privacy protection and break "data silos", and protects all data.

• Information Systems Review
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• v.24 no.3
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• pp.69-91
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• 2022

The video recommendation services help to save the user's information search time in the overflowing online information, and algorithms for more efficient and accurate recommendation are continuously developed. In particular, TikTok has the largest number of users in the short video industry due to its unique recommendation algorithms. In this study, by applying a privacy calculation model, the research tried to compare users' responses to each type of TikTok's recommendation service. Users are well aware of the privacy concerns and benefits of TikTok's recommendation service. Although there is a risk, it was found that users continue to use TikTok's recommendation service because the benefits are greater.

• Journal of Digital Convergence
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• v.15 no.3
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• pp.187-193
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• 2017

Objects Internet-based healthcare services provide healthcare and healthcare services, including measurement of user's vital signs, diagnosis and prevention of diseases, through a variety of object internet devices. However, there is a problem that new security vulnerability can occur when inter-working with the security weakness of each element technology because the internet service based on the object Internet provides a service by integrating various element technologies. In this paper, we propose a user privacy protection model that can securely process user's healthcare information from a third party when delivering healthcare information of users using wearable equipment based on IoT in a mobile environment to a server. The proposed model provides attribute values for each healthcare sensor information so that the user can safely handle, store, and store the healthcare information, thereby managing the privacy of the user in a hierarchical manner. As a result of the performance evaluation, the throughput of IoT device is improved by 10.5% on average and the server overhead is 9.9% lower than that of the existing model.

• Journal of Convergence for Information Technology
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• v.10 no.4
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• pp.18-24
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• 2020

Recently, research on Society 5.0 has been actively carried out in Japan. The Society 5.0 is used in various areas using IoT sensors. This paper proposes a privacy approach model of multiple approaches to IoT users based on Society 5.0. The proposed model used multiple methods of synchronizing important information of IoT devices with one another in the virtual environment. The proposed model improved the efficiency of IoT information by accumulating the weight of IoT information on a probability-based basis. Further, it improves the accuracy of IoT information by segmenting it so that attribute information is linked to IoT information. As a result of the performance evaluation, the efficiency of IoT devices has improved by an average of 5.6 percent, depending on the number of IoT devices and the number of IoT hub devices. Accuracy has improved by an average of 15.9% depending on information collection and processing.