• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.77-85
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• 2022

Unlike previous studies that focused on the diversity of YouTube content, this study tried to identify factors affecting users' satisfaction with the YouTube recommendation system. Specifically, by adding content preference suitability and privacy concerns to the technology acceptance model, we empirically analyzed how these variables affect user's satisfaction of the YouTube AI recommendation system. For this purpose, asurvey was conducted on college students in their 20s and 30s, and the main research results are as follows. First, in the respondents of this study, playfulness and usefulness, which are major variables of the technology acceptance model, appeared as significant factors affecting the satisfaction of the YouTube AI recommendation system, whereas the effect of ease to use was not found. Second, content preference suitability was found to affect the satisfaction with AI recommendation system, but privacy concerns did not affect the satisfaction with YouTube AI recommendation system. Based on these research results, the implications of the study and the directions for future studies were suggested.

• Journal of KIISE
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• v.45 no.1
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• pp.45-52
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• 2018

With the advent of BCI technology in recent years, various BCI products have been released. BCI technology enables brain information to be transmitted directly to a computer, and it will bring a lot of convenience to life. However, there is a problem with information protection. In particular, EEG data can raise issues about personal privacy. Collecting and analyzing big data on EEG reports raises serious concerns about personal information exposure. In this paper, we propose a secure privacy-preserving BCI model in a big data environment. The proposed model could prevent personal identification and protect EEG data in the cloud environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.3
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• pp.503-512
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• 2020

The revisions to data privacy acts allows the disclosure of data after anonymizing personal information. Such anonymized data is expected to be useful in research and services, but there are high concerns about privacy breaches such as re-identifying of the individuals from the anonymized data. In this paper, we showed that identifying individuals from public data is not very difficult, and also raises questions about the reliability of the public data. We suggest that users understand the trade-offs between data disclosure and privacy protection so that they can use data securely under the revised data privacy acts.

• Informatization Policy
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• v.25 no.2
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• pp.3-19
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• 2018

With the introduction of video cameras into law enforcement, a great deal of police organizations have adopted the technology in their routine crime prevention activities. The up-to-date systems of ambient surveillance energized by CCTV, police wearable cameras, drones, and thermal imaging devices enable the police to thoroughly monitor public spaces as well as to rigorously arrest on-scene criminals. These efforts to improve the level of surveillance are often met with public resistance raising concerns over citizens' rights to privacy. Recent studies on the use of police video equipment have constantly raised the issues related to the lack of applicable legal provisions, risk of personal information and privacy infringement as well as security vulnerabilities. In this regard, the present study attempted to review the public surveillance methods currently used by law enforcement agencies worldwide within the context of public safety and individual rights to privacy. Furthermore, the present study also discussed the legal boundaries of police use of video equipment to address public concerns over privacy issues.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2827-2848
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• 2021

Mobile Crowdsourcing (MCS) has become an emerging paradigm evolved from crowdsourcing by employing advanced features of mobile devices such as smartphones to perform more complicated, especially spatial tasks. One of the key procedures in MCS is to collect answers from mobile users (workers), which may face several security issues. First, authentication is required to ensure that answers are from authorized workers. In addition, MCS tasks are usually location-dependent, so the collected answers could disclose workers' location privacy, which may discourage workers to participate in the tasks. Finally, the overhead occurred by authentication and privacy protection should be minimized since mobile devices are resource-constrained. Considering all the above concerns, in this paper, we propose a lightweight and privacy-preserving answer collection scheme for MCS. In the proposed scheme, we achieve anonymous authentication based on traceable ring signature, which provides authentication, anonymity, as well as traceability by enabling malicious workers tracing. In order to balance user location privacy and data availability, we propose a new concept named current location privacy, which means the location of the worker cannot be disclosed to anyone until a specified time. Since the leakage of current location will seriously threaten workers' personal safety, causing such as absence or presence disclosure attacks, it is necessary to pay attention to the current location privacy of workers in MCS. We encrypt the collected answers based on timed-release encryption, ensuring the secure transmission and high availability of data, as well as preserving the current location privacy of workers. Finally, we analyze the security and performance of the proposed scheme. The experimental results show that the computation costs of a worker depend on the number of ring signature members, which indicates the flexibility for a worker to choose an appropriate size of the group under considerations of privacy and efficiency.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.1
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• pp.209-226
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• 2016

Recently, there is a growing interest in Fintech which is a business based on using IT to provide financial services. At the early stage of diffusion of Fintech, one of the issues raised is the concern for information security. This study examines actual users' information privacy concern and user resistance to Fintech services. We also investigates the effects of social influence and mobile Internet literacy on information privacy concern and user resistance. In particular, this research verifies the interaction effect between regulatory focus and information privacy concern to influence user resistance. Based on the findings, the results of this study provide strategic implications for firms which attempt to reduce user resistance to Fintech services and proliferate Fintech usage.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12B
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• pp.743-749
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• 2007

The problem of privacy is considered one of the main concerns to deploy RFID applications. In this paper, we propose methods to change a tag state and assign a master leader for the protection of privacy. By changing a tag state, we can limit the range for the information retrieval of the tag to all leaders or a specific leader (mater leader). Whenever the owner of a tag changes, with the master leader assignment method for the tag, we can make only the master leader get the information for the tag. With the proposed methods, it is expected that the privacy problems can be solved by preventing the private information of tags that persons have from being exposed by illegal leaders.

• Journal of Intelligence and Information Systems
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• v.15 no.2
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• pp.97-111
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• 2009

Context-aware computing, as a core of smart space development, has been widely regarded as useful in realizing individual service provision. However, most of context-aware services so fat are in its early stage to be dispatched for actual usage in the real world, caused mainly by user's privacy concerns. Moreover, since legacy context-aware services have focused on acquiring in an automatic manner the extra-personal context such as location, weather and objects near by, the services are very limited in terms of quality and variety if the service should identify intra-personal context such as attitudes and privacy concern, which are in fact very useful to select the relevant and timely services to a user. Hence, the purpose of this paper is to propose a novel methodology to infer the user's privacy concern as intra-personal context in an intelligent manner. The proposed methodology includes a variety of stimuli from outside the person and then performs model-based reasoning with social theory models from model base to predict the user's level of privacy concern semi-automatically. To show the feasibility of the proposed methodology, a survey has been performed to examine the performance of the proposed methodology.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.2
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• pp.15-34
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• 2009

Today the u-government services are becoming more personalized and intelligent. For the successful implementation of personalization, individual user's privacy concerns must be respected and taken care of. Based on the empirical survey results, this research summarizes the reluctance to the government's use of private information using six categories. We measure user's psychological distance toward e-government using the four levels, adopting the suggestions by the Proxemics. Since a positive correlation is Identified between people's psychological Intimacy toward e-government and their tolerance to the use of private Information, the amount and/or types of private information should be sequentially used in personalization systems. Initially allowing the least intolerable private information such as occupation information, the personalization system should additionally use the next tolerable Information such as health information or service request/interest information, as user's psychological distance toward government services becomes shorter.

• Journal of Korea Multimedia Society
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• v.18 no.4
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• pp.499-505
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• 2015

Security supports are a significant factor in the design of mobile ad hoc networks. In the dynamic topology where the node changes frequently, private key generation and revocation for newly joining and leaving nodes must be considered. In addition, the identities of individual nodes must be protected as well in mobile networks to avoid personal privacy concerns. This paper proposes ID-based private key revocation scheme and non-interactive key agreement scheme in anonymous MANETs. The proposed scheme provides the user privacy using pseudonyms and private key generation and revocation schemes with consideration of dynamic user changes. Therefore, our schemes can be applied in dynamic and privacy-preserving MANETs which are helpful to share multimedia data.