• The Journal of the Korea Contents Association
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• v.10 no.9
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• pp.57-67
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• 2010

Smart grid technology can expand energy efficiency into the home by monitoring consumer energy usage in real time and communicating with household devices that respond to demands to shut off during periods of non-use, allowing individual consumers to control their electricity usage more effectively. But, the information collected on a smart grid will form a library of personal information, the mishandling of which could be highly invasive of consumer privacy. There will be major concerns if consumer-focused principles of transparency and control are not treated as essential design principles from beginning to end. In this paper, using. All-Or-Nothing Transform encryption mode for providing smart grid security, we propose efficient distributed data Management based on XOR operation. The contribution of this paper is to provide a secure algorithm that manages efficiently distributed data in the field of private data in smart grid environment.

• The Journal of Society for e-Business Studies
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• v.9 no.3
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• pp.39-56
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• 2004

This study introduces consumer protection policies at domestic and overseas, regarding the current situation that is raised about, and analyzes how to promote e-commerce with consumer protection oriented. This article explores e-commerce protection policies aiming at enforcing consumer protection and introduces some strategies - enhancing consumer trust, improving electronic transaction disputation, personal information security and privacy and using authorized certificate. This paper aims at suggesting the method of promoting e-commerce through ensuring the consumer trust and decreasing the transaction cost.

• Journal of Korea Multimedia Society
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• v.15 no.9
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• pp.1126-1132
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• 2012

To enhance network efficiency, CCN allow intermediate network nodes between a content consumer and a content publisher to temporarily cache transmitted contents. Then the network nodes immediately return back the cached contents to another consumers when the nodes receives relevant contents request messages from the consumers. For that, CCN utilizes hierarchical content names to forward a request message as well as a response message. However, such content names semantically contain much information about domain/user as well as content itself. So it is possible to invade users' privacy. In this paper, we first review both the problem of CCN name in the view point of privacy and proposed schemes. Then we propose an improved name management scheme for users' privacy preservation.

• The Journal of Information Systems
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• v.32 no.2
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• pp.1-24
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• 2023

Purpose The aim of this study is to investigate how system quality, privacy concerns, and usefulness impact user satisfaction and word-of-mouth intention towards smart order services among Chinese consumers. The study also seeks to provide both theoretical and practical implications based on the findings. Design/methodology/approach This study conducted an empirical study on Chinese consumers through an online survey on 274 users of smart order service in China. To analyze the data, frequency analysis, reliability analysis, and confirmatory factor analysis were performed using SPSS 26.0 and AMOS 26.0 statistical programs, and structural equation model was used for hypothesis testing. Findings The study results are as follows. First, system quality was found to have a positive effect on usefulness and user satisfaction. Second, privacy concerns were found to have a positive effect on user satisfaction, but not on usefulness. Third, user satisfaction was found to have a positive effect on consumers' word-of-mouth intention of the smart order service. Finally, mediating effects were found between system quality and user satisfaction through usefulness, as well as between system quality, perceived privacy concern, and usefulness through user satisfaction.

• Human Ecology Research
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• v.51 no.5
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• pp.483-495
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• 2013

This study aimed to identify the dimensions of benefits and costs that consumers perceive in utilizing locationbased applications (LBAs) on smartphones, and to distinguish consumer groups according to their perceptions of those benefits and costs. A web-based consumer survey was conducted-among consumers who had experience using LBAs. Four hundred participants were 20's to 40's, with 200 women and 200 men. Descriptive statistics, frequency analysis, t -tests, one-way analysis of variance, and cluster analysis were used for data analysis. The findings of this study are as follows: first, LBAs accounted for about 20% of the smartphone apps used by consumers. Second, factor analysis identified the underlying dimensions of the benefits and costs of smartphone LBAs. The underlying dimensions of benefits perceived by consumers were information/economic/convenience, entertainment and personalization. Privacy concerns, lack of trust and lack of behavioral control were the underlying dimensions of the perceived costs of LBAs. Third, ANOVA showed that the perceived benefits and costs of smartphone LBA services differed according to the characteristics of the consumer. Cluster analysis identified three distinctive consumer groups according to the levels of perceive costs and benefits of smartphone LBAs. The three groups were labeled the 'benefit-cost balanced group,' 'cost centered group,' and 'benefit centered group.'

• The Korean Journal of Food & Health Convergence
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• v.10 no.1
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• pp.1-6
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• 2024

Purpose: The research aims to address the intricacies of AI and Big Data application within the food industry. This study explores the strategic implementation of AI and Big Data in the food industry. The study seeks to understand how these technologies can be employed to bolster consumer engagement and contribute to market expansion, while considering ethical implications. Research Method: This research employs a comprehensive approach, analyzing current trends, case studies, and existing academic literature. It focuses on the application of AI and Big Data in areas such as supply chain management, consumer behavior analysis, and personalized marketing strategies. Results: The study finds that AI and Big Data significantly enhance market analytics, consumer personalization, and market trend prediction. It highlights the potential of these technologies in creating more efficient supply chains, improving consumer satisfaction through personalization, and providing valuable market insights. Conclusion and Implications: The paper offers actionable insights and recommendations for the effective implementation of AI and Big Data strategies in the food industry. It emphasizes the need for ethical considerations, particularly in data privacy and the transparency of AI algorithms. The study also explores future trends, suggesting that AI and Big Data will continue to revolutionize the industry, emphasizing sustainability, efficiency, and consumer-centric practices.

• Journal of Information Processing Systems
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• v.7 no.1
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• pp.111-120
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• 2011

The concept of Smart-Homes is becoming more and more popular. It is anticipated that Radio Frequency IDentification (RFID) technology will play a major role in such environments. We can find many previously proposed schemes that focus solely on: authentication between the RFID tags and readers, and user privacy protection from malicious readers. There has also been much talk of a very popular RFID application: a refrigerator/bookshelf that can scan and list out the details of its items on its display screen. Realizing such an application is not as straight forward as it seems to be, especially in securely deploying such RFID-based applications in a smart home environment. Therefore this paper describes some of the RFID-based applications that are applicable to smart home environments. We then identify their related privacy and security threats and security requirements and also propose a secure approach, where RFID-tagged consumer items, RFID-reader enabled appliances (e.g., refrigerators), and RFID-based applications would securely interact among one another. At the moment our approach is just a conceptual idea, but it sheds light on very important security issues related to RFID-based applications that are beneficial for consumers.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1499-1508
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• 2018

Although fast-growing e-commerce markets gave a lot of companies opportunities to expand their customer bases, it is also the case that there are growing number of cases in which the so-called 'black consumers' cause much damage on many companies. In this study, we will implement and optimize a machine learning model that detects black consumers using customer data from e-commerce store. Using filter method for feature selection and 4 different algorithms for classification, we could get the best-performing machine learning model that detects black consumer with F-measure 0.667 and could also yield improvements in performance which are 11.44% in F-measure, 10.51% in AURC, and 22.87% in TPR.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.253-258
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• 2021

In this study, we explored consumers' the privacy attitudes and Internet activities on the expectations of the fourth industrial revolution. Furthermore, we examined the moderating effect of Internet activities between the privacy attitudes and the expectations of the fourth industrial revolution. Research data are 2018 Korea media panel survey provided by Korea Information Society Development Institute. As a result, concerns about privacy were negative on the expectations of the fourth industrial revolution. Consumer's internet activities had a positive effect on the expectations of the fourth industrial revolution. Concerns about privacy have a negative effect on the expectations of the fourth industrial revolution, but active internet activities have mitigated it or turned it into a positive. This study will contribute as basic data for more active responses in the economic structure facing the 4th industrial revolution.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.4
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• pp.3-12
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• 2006

RFID (Radio Frequency Identification) system is expected to play a critical role providing widespread services in the ubiquitous period. However, widespread use of RFID tags may create new threats to the privacy of individuals such as information leakage and traceability. It is difficult to solve the privacy problems because a tag has the limited computing power that is not the adequate resource to support the general encryption. Although the scheme of [2] protects the consumer privacy using an external agent, a tag should compute exponential operation needed high cost. We propose Self Re-Encryption Protocol (SREP) which provides song privacy without assisting of any external agent. Our SREP is well suitable to low-cost RFID system since it only needs multiplication and exclusive-or operation.