• Journal of Digital Convergence
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• v.13 no.4
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• pp.219-225
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• 2015

There has been an exponential growth in the distribution and possession of sensitive information because of the emergence of various information channels such as smart devices, social media, etc. This enables the internet based web or mobile service operation institutions collecting the more personal information with ease, and in turn causes the issues of the privacy concerns. Followings are the results of this study: First, the information privacy concern has the negative effects upon the trust. Second, the information privacy concern has the negative effects upon the provision intention of personal information and the trust has positive effects upon the offering intention of personal information. At last, the offering intention of the personal information has the positive effects upon the behavior to provide the personal information.

• Journal of Information Technology Services
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• v.17 no.3
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• pp.157-169
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• 2018

This study aims to examine the factors influencing user attitude toward Smart Home service as the demand of Smart Home service is increasing and it somewhat involves privacy risk. To this end, the research model includes five independent variables, trust in service provider, perceived privacy risk, self efficacy, interpersonal influence, and external influence, influencing the attitude toward Smart Home service. So, this study aims to analyze which variable is the most critical and influential among the five factors and suggest the direction of Smart Home industries. This study first reviews the literature on Smart Home services and describes its Korean situation. Data were collected from residents living in a smart apartment complex. The results show that (1) users have a very positive attitude toward Smart Home service in total, (2) trust in service providers, self efficacy, and interpersonal influence positively impact user attitude toward Smart Home service and interpersonal influence is the most influential variable, however, (3) perceived privacy risk and external influence dose not significantly impact it. These results imply that the role of service providers, self efficacy, and interpersonal influence are important factors on the user attitude toward Smart Home service. Finally, the study's findings and limitations are discussed and potential avenues for future research are suggested.

• Asia pacific journal of information systems
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• v.27 no.3
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• pp.156-175
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• 2017

The proposed conceptual framework is based in the relationships among knowledge of personal information security, trust on the personal information security policies of parcel delivery service companies, privacy concern, trust in and risk of parcel delivery services, and user satisfaction with parcel delivery services. Drawing upon both cognitive theory of emotion and cognitive emotion theory that complement each other, we propose a research model and examine the relationships between cognitive and emotional factors and the usage of parcel delivery services. The proposed model is validated using data from customers who have previously used parcel delivery services. The results show a significant relationship between the cognitive and affective factors and the usage of parcel delivery services. This study enhances our understanding of parcel delivery services based on the consumers' psychological processes and presents useful implications on the importance of privacy and security in these services.

• Asia pacific journal of information systems
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• v.31 no.2
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• pp.236-256
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• 2021

Online financial technology products are an important consumer finance innovation. While a large body of previous research has focused on initial adoption and consumer willingness to use these products, little research explores the continued use of these products beyond the initial adoption phase. In particular, special attention should be paid to how users' trust and perceptions of privacy and security affect continued use behavior. This paper integrates the expectation confirmation model of information system continuance (ECM-ISC), the information system success model (ISSM) and the security and trust literatures to investigate continued use of online financial technology. To test the research model, we collected 398 valid questionnaires from Ant Credit Pay users. The research results show that system and service quality positively impact users' expectation confirmation, while information quality has no significant impact. Expectation confirmation and perceived usefulness positively affect user satisfaction. Moreover, the user's perception of privacy and security plays a vital role in user satisfaction. Satisfaction and perceived trust jointly promote users' continuance behaviors. Findings of this study indicates the importance of the information system success factors and security factors due to their influence on the continued use of Fintech products. This conclusion has implications for enterprises in improving the product qualities and enhancing the degree of security to meet user needs.

• Informatization Policy
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• v.30 no.2
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• pp.22-45
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• 2023

In research on the use of AI-based voice assistant services, problems related to the user's trust and privacy protection arising from the experience of service use are constantly being raised. The purpose of this study was to investigate empirically the effects of individual trust in AI and online privacy concerns on the continued use of AI-based voice assistants, specifically the impact of their interaction. In this study, question items were constructed based on previous studies, with an online survey conducted among 405 respondents. The effect of the user's trust in AI and privacy concerns on the adoption and continuous use intention of AI-based voice assistant services was analyzed using the Heckman selection model. As the main findings of the study, first, AI-based voice assistant service usage behavior was positively influenced by factors that promote technology acceptance, such as perceived usefulness, perceived ease of use, and social influence. Second, trust in AI had no statistically significant effect on AI-based voice assistant service usage behavior but had a positive effect on continuous use intention. Third, the privacy concern level was confirmed to have the effect of suppressing continuous use intention through interaction with trust in AI. These research results suggest the need to strengthen user experience through user opinion collection and action to improve trust in technology and alleviate users' concerns about privacy as governance for realizing digital government. When introducing artificial intelligence-based policy services, it is necessary to disclose transparently the scope of application of artificial intelligence technology through a public deliberation process, and the development of a system that can track and evaluate privacy issues ex-post and an algorithm that considers privacy protection is required.

• International Journal of Contents
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• v.6 no.3
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• pp.15-18
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• 2010

Grid system is based on the Grid Security Infrastructure (GSI). GSI uses user's proxy to guarantee availability among multi-trust domains. Since grid system has been developed focusing on availability, GSI provides authentication and authorization performed by systems, but there are lacks of privacy consideration. For this reason, some researchers decide to use their own cluster system and do not want to use public grid systems. In this paper, we introduce a new privacy enhanced security mechanism for grid systems. With this mechanism, user can participate in resource allocation and authorization to user's contents more actively. This mechanism does not need to change previous middleware and minimize the computational overheads.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.970-975
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• 2006

There is a tradeoff between user's privacy and utility of context-aware services in ubiquitous computing environments. Many privacy models have been proposed to support the disclosure of personal information at different levels of detail, in ubiquitous computing environments. However, most of these models do not allow for explicit criteria to assess the benefit users are likely to reap by disclosing their personal information. In this paper, we propose an automated decision making mechanism that evaluates the "benefit of disclosure" for the users based on trust relationships between users and information requesters and manages the disclosure of user's personal information accordingly. Unlike other trust models, we do not regard the reputation of an information requester as sufficient to determine his/her trustworthiness. Instead, we represent trustworthiness as a function of information requester's reputation in the eyes of the user and his/her competence in a given context. To validate our mechanism, we apply it to context-aware healthcare application that monitors physiological condition of a user.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.3
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• pp.487-499
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• 2022

Machine learning such as deep learning have been widely used in recent years. Recently deep learning is performed in a trusted execution environment such as ARM TrustZone to improve security in edge devices and embedded devices with low computing resource. To mitigate this problem, we propose TPMP that efficiently uses the limited memory of TEE through DNN model partitioning. TPMP achieves high confidentiality of DNN by performing DNN models that could not be run with existing memory scheduling methods in TEE through optimized memory scheduling. TPMP required a similar amount of computational resources to previous methodologies.

• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.49-65
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• 2018

The purpose of the research is to identify the effects of brand evidence, brand personality and negative factors on extended brand trust and customer purchase intention in IoT (Internet of Things) service. Negative factors include scarcity marketing and privacy concern. To achieve this objective, we analyzed the 269 respondents who had used Xiaomi products at least more than once. The results of this study are as follows: First, it was found that core service, self-image congruence of brand evidence and brand personality has a positive influence on extended brand trust. But, perceived price of brand evidence is not related to extended brand trust. Secondly, Scarcity marketing influenced extended brand trust. But, Privacy concern is not related to extended brand trust. Consumers did not realize privacy because of technological innovation of IoT. Thus, the research has a different significance from antecedent research.

• Convergence Security Journal
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• v.23 no.5
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• pp.9-19
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• 2023

Smart cars, which incorporate information and communication technologies (ICT) to improve driving safety and convenience for drivers, have recently emerged. However, the increasing risk of automotive cybersecurity due to the vulnerability of electronic control units (ECUs) and automotive networks, which are essential for realizing the autonomous driving functions of smart cars, is a major obstacle to the widespread adoption of smart cars. Although there have been only a few real-world cases of smart car hacking, drivers' concerns about the security of smart cars can have a negative impact on their proliferation. Therefore, it is important to understand the risk factors perceived by drivers and the trust in smart cars formed through them in order to promote the future diffusion of smart cars. This study examines the risk factors that affect the formation of trust in smart cars, focusing on security and privacy, and analyzes how these factors affect safety perceptions and trust in smart cars.