• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1462-1477
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• 2024

With the evolving complexity of connected vehicle features, the volume and diversity of data generated during driving continue to escalate. Enabling data sharing among interconnected vehicles holds promise for improving users' driving experiences and alleviating traffic congestion. Yet, the unintentional disclosure of users' private information through data sharing poses a risk, potentially compromising the interests of vehicle users and, in certain cases, endangering driving safety. Federated learning (FL) is a newly emerged distributed machine learning paradigm, which is expected to play a prominent role for privacy-preserving learning in autonomous vehicles. While FL holds significant potential to enhance the architecture of the Internet of Vehicles (IoV), the dynamic mobility of vehicles poses a considerable challenge to integrating FL with vehicular networks. In this paper, a novel clustered FL framework is proposed which is efficient for reducing communication and protecting data privacy. By assessing the similarity among feature vectors, vehicles are categorized into distinct clusters. An optimal vehicle is elected as the cluster head, which enhances the efficiency of personalized data processing and model training while reducing communication overhead. Simultaneously, the Local Differential Privacy (LDP) mechanism is incorporated during local training to safeguard vehicle privacy. The simulation results obtained from the 20newsgroups dataset and the MNIST dataset validate the effectiveness of the proposed scheme, indicating that the proposed scheme can ensure data privacy effectively while reducing communication overhead.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.8
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• pp.853-862
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• 2010

As the mobile device and broadband wireless internet such as WiBro, HSDPA is widely spreading, various types of advertisement and services based on personal location information can be provided. However, with convenience supported by these services, it is possible to be increased an invasion of privacy such as personal location and moving pattern. In this paper, we analysis an essential element for protection of privacy related on location information in mobile environment and propose location privacy protocol for managing location privacy self-control. And we design and implementation prototype of location privacy self-control system which is able to manage user's location privacy condition oneself using the proposed location privacy protocol.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.899-900
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• 2012

RFID technology can help automatically and remotely identify objects, which raises many security concerns. We review and categorize several RFID security and privacy solutions, and conclude that the most promising and low-cost approach currently attracts little academic attention. We therefore concluded that, from a privacy perspective, the user scheme is an important strategy for meeting the consumer's needs. Furthermore, we call for the privacy research community to put more effort into this line of thinking about RFID privacy.

• Journal of Convergence for Information Technology
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• v.9 no.7
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• pp.1-7
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• 2019

With the recent commercialization of the next generation of wireless 5G in everyday life, many changes have been made to organizations, industries and businesses of various sizes in various fields. However, although the improved speed and latency of 5G has improved, improvements in encryption, authentication and privacy are still required. In this paper, multiple groups of information management techniques are proposed to efficiently protect users' privacy in the heterogeneous environment of 5G. The proposed technique aims to allow distributed management of users' privacy links by clouding the privacy information generated by different heterogeneous devices to efficiently interface with different groups. Suggestion techniques process user-specific privacy information independently in a virtual space so that users can periodically synchronize their privacy information.

• The Journal of Information Systems
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• v.16 no.3
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• pp.21-44
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• 2007

Internet privacy is named as one of the major barriers to the expansion and further development of e-commerce. This study is to identify the antecedents to Internet privacy concerns, to investigate the relationship of the antecedents and the perceived trust and to validate Internet privacy's effect on the perceived trust. A conceptual model which identifies Internet literacy and perceived vulnerability as antecedents to Internet privacy concern is proposed and tested based on the sample of 276 Internet users. Empirical findings show that Internet literacy affect Internet privacy concern negatively while perceived vulnerability affect positively. Also perceived vulnerability's effect on and privacy concern's effect on perceived trust has both directional negative support. Implications and further research agenda are provided with the limitation of the study.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.185-187
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• 2015

Increasingly important user based service on the smart media era, and increasing awareness about the user experience. As the connected Internet information systems increases, one of the problems happening between users and information systems such as Internet shopping-malls, portal sites, and corporate web sites is related with the information privacy concerns issues. In this research, we aim to analyze factors influencing of the invasion of privacy on continue using intention in online environment. Based on these findings, several theoretical and practical implications were suggested and discussed. Thus, we have reviewed extensive previous studies on information privacy in local and foreign information systems, marketing and other fields. The purpose of this study is to provide future directions of studies on information privacy concerns by analyzing past and recent trends of the studies.

• International Journal of Contents
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• v.13 no.1
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• pp.22-30
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• 2017

The diffusion of advanced mobile technology has introduced new types of personal information or 'location data'. These new data mean new opportunities for businesses, such as location-based services (LBS), but have resulted in new consumer anxieties regarding disclosure of personal information. This study examines the effects of the consumers' perceived control over "time-andplace" information in location-aware services on their perceived privacy risk. A total of 270 respondents participated in this study. Conditions of perceived privacy control were operationalized over time-and-place information, in a $2{\times}2$ factorial design. Results indicate that the perceived control over time-and-place personal information is a significant predictor of perceived risk, and control assurances over time-and-place information enhances the perception of control, thus alleviating the perceived risk. In addition, the effect is much more significant when time and place were combined.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.125-139
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• 2013

Big data refers to the data that cannot be processes with conventional contemporary data technologies. As smart devices and social network services produces vast amount of data, big data attracts much attention from researchers. There are strong demands form governments and industries for bib data as it can create new values by drawing business insights from data. Since various new technologies to process big data introduced, academic communities also show much interest to the big data domain. A notable advance related to the big data technology has been in various fields. Big data technology makes it possible to access, collect, and save individual's personal data. These technologies enable the analysis of huge amounts of data with lower cost and less time, which is impossible to achieve with traditional methods. It even detects personal information that people do not want to open. Therefore, people using information technology such as the Internet or online services have some level of privacy concerns, and such feelings can hinder continued use of information systems. For example, SNS offers various benefits, but users are sometimes highly exposed to privacy intrusions because they write too much personal information on it. Even though users post their personal information on the Internet by themselves, the data sometimes is not under control of the users. Once the private data is posed on the Internet, it can be transferred to anywhere by a few clicks, and can be abused to create fake identity. In this way, privacy intrusion happens. This study aims to investigate how perceived personal information overload in SNS affects user's risk perception and information privacy concerns. Also, it examines the relationship between the concerns and user resistance behavior. A survey approach and structural equation modeling method are employed for data collection and analysis. This study contributes meaningful insights for academic researchers and policy makers who are planning to develop guidelines for privacy protection. The study shows that information overload on the social network services can bring the significant increase of users' perceived level of privacy risks. In turn, the perceived privacy risks leads to the increased level of privacy concerns. IF privacy concerns increase, it can affect users to from a negative or resistant attitude toward system use. The resistance attitude may lead users to discontinue the use of social network services. Furthermore, information overload is mediated by perceived risks to affect privacy concerns rather than has direct influence on perceived risk. It implies that resistance to the system use can be diminished by reducing perceived risks of users. Given that users' resistant behavior become salient when they have high privacy concerns, the measures to alleviate users' privacy concerns should be conceived. This study makes academic contribution of integrating traditional information overload theory and user resistance theory to investigate perceived privacy concerns in current IS contexts. There is little big data research which examined the technology with empirical and behavioral approach, as the research topic has just emerged. It also makes practical contributions. Information overload connects to the increased level of perceived privacy risks, and discontinued use of the information system. To keep users from departing the system, organizations should develop a system in which private data is controlled and managed with ease. This study suggests that actions to lower the level of perceived risks and privacy concerns should be taken for information systems continuance.

• 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 information and communication convergence engineering
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• v.9 no.4
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• pp.441-446
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• 2011

Radio frequency identification (RFID) tags are cheap and simple devices that can store unique identification information and perform simple computation to keep better inventory of packages. Security protocol for RFID tags is needed to ensure privacy and authentication between each tag and their reader. In order to accomplish this, in this paper, we analyzed a lightweight privacy and authentication protocol for passive RFID tags.