• Journal of the Korea Society of Computer and Information
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• v.25 no.1
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• pp.151-157
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• 2020

This study explored the moderating effects of security ability on the influence of privacy concerns on internet activity using Korea media panel survey data. To this end, we applied between-subjects factorial design between 2 (privacy concern high / low) × 2 (security ability high / low) groups and compared five types of internet activity among four groups by variance analysis. As a result, privacy concerns have a main effect on internet activity, and security ability have a moderating role in this relationship. Despite the privacy concerns, people do their internet activities in order to enjoy the benefit from the internet. This study have academic implication in that it focus on the issue of privacy paradox in terms of the type of internet activity. In addition, practical implications are that, in order to activate online activities of individuals in an internet-connected society, efforts for enhancing their security abilities are necessary.

• 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.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.99-108
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• 2024

The Internet of Things (IoT) is a novel concept that allows a large number of objects to be connected to the Internet while also allowing them to be controlled remotely. The Internet of Things is extensive and has become an almost inseparable part of our daily lives. Users' personal data is frequently obtained by these linked gadgets and stored online. In recent years, the security of acquired data has become a major concern. As devices grow more linked, privacy and security concerns grow more pressing, and they must be addressed as soon as possible. IoT implementations and devices are particularly vulnerable to attacks that might adversely affect customer security and privacy, which might have an impact on their practical utility. The goal of this study is to bring attention to the security and privacy concerns that exist in IoT systems. To that purpose, the paper examines security challenges at each level of the IoT protocol stack, identifies underlying impediments and critical security requirements, and provides a rapid overview of available security solutions for securing IoT in a layered environment.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.43-55
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• 2021

The amount of Big Data generated from multiple sources is continuously increasing. Traditional storage methods lack the capacity for such massive amounts of data. Consequently, most organizations have shifted to the use of cloud storage as an alternative option to store Big Data. Despite the significant developments in cloud storage, it still faces many challenges, such as privacy and security concerns. This paper discusses Big Data, its challenges, and different classifications of security and privacy challenges. Furthermore, it proposes a new classification of Big Data security and privacy challenges and offers some perspectives to provide solutions to these challenges.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.97-104
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• 2022

In recent years, data privacy has become increasingly important. The goal of network cryptography is to protect data while it is being transmitted over the internet or a network. Social media and smartphone apps collect a lot of personal data which if exposed, might be damaging to privacy. As a result, sensitive data is exposed and data is shared without the data owner's consent. Personal Information is one of the concerns in data privacy. Protecting user data and sensitive information is the first step to keeping user data private. Many applications user data can be found on other websites. In this paper, we discuss the issue of privacy and suggest a mechanism for keeping user data hidden in other applications.

• 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.

• Asia pacific journal of information systems
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• v.30 no.4
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• pp.919-945
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• 2020

Social media platforms such as Instagram and Facebook lead to potential security risks, which consequently raise public concerns about privacy. However, most people rarely make active efforts to protect their personal data, even though they have shown increasing concerns about privacy. Therefore, this study examines the factors that determine social media users' behavior of using privacy settings and testifies the existence of privacy paradox in such a context. In addition, it investigates the mediating effects of implementation intentions on the relationship between intentions and behaviors. In the study, we collected data through questionnaires, and the respondents were undergraduate and graduate students in South Korea. After a pilot test (n = 92) and a set of face-to-face interviews, 266 usable responses were retrieved for data analysis finally. The results confirmed the existence of the privacy paradox regarding the use of social media privacy settings. And the implication intention did positively mediate the relationship between intention and behavior in the context of social media privacy settings. To the best of our knowledge, our study is the first in the information privacy literature to introduce the notion of implementation intention which is a much more powerful explanation and prediction of actual behavior than the (behavioral) intention.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.25-31
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• 2023

Fog computing diversifies cloud computing by using edge devices to provide computing, data storage, communication, management, and control services. As it has a decentralised infrastructure that is capable of amalgamating with cloud computing as well as providing real-time data analysis, it is an emerging method of using multidisciplinary domains for a variety of applications; such as the IoT, Big Data, and smart cities. This present study provides an overview of the security and privacy concerns of fog computing. It also examines its fundamentals and architecture as well as the current trends, challenges, and potential methods of overcoming issues in fog computing.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.340-350
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• 2022

The big data term refers to the great volume of data and complicated data structure with difficulties in collecting, storing, processing, and analyzing these data. Big data analytics refers to the operation of disclosing hidden patterns through big data. This information and data set cloud to be useful and provide advanced services. However, analyzing and processing this information could cause revealing and disclosing some sensitive and personal information when the information is contained in applications that are correlated to users such as location-based services, but concerns are diminished if the applications are correlated to general information such as scientific results. In this work, a survey has been done over security and privacy challenges and approaches in big data. The challenges included here are in each of the following areas: privacy, access control, encryption, and authentication in big data. Likewise, the approaches presented here are privacy-preserving approaches in big data, access control approaches in big data, encryption approaches in big data, and authentication approaches in big data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.3
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• pp.411-427
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• 2010

Data sharing is an essential process for collaborative works particularly in the banking, finance and healthcare industries. These industries require many collaborative works with their internal and external parties such as branches, clients, and service providers. When data are shared among collaborators, security and privacy concerns becoming crucial issues and cannot be avoided. Privacy is an important issue that is frequently discussed during the development of collaborative systems. It is closely related with the security issues because each of them can affect the other. The tradeoff between privacy and security is an interesting topic that we are going to address in this paper. In view of the practical problems in the existing approaches, we propose a collaborative framework which can be used to facilitate concurrent operations, single point failure problem, and overcome constraints for two-party computation. Two secure computation protocols will be discussed to demonstrate our collaborative framework.