• Journal of Digital Convergence
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• v.11 no.11
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• pp.143-153
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• 2013

Big data is expected to bring forth enormous public good as well as economic opportunity. However there is ongoing concern about privacy not only from public authorities but also from private enterprises. Big data is suspected to aggravate the existing privacy battle ground by introducing new types of privacy risks such as privacy risk of behavioral pattern. On the other hand, big data is asserted to become a new way to by-pass tradition behavioral tracking such as cookies, DPIs, finger printing${\cdots}$ and etc. For it is not based on a targeted person. This paper is to find out if big data could contribute to catching out behavioral patterns of consumers without threatening or damaging their privacy. The difference between traditional behavioral tracking and big data analysis from the perspective of privacy will be discerned.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.5
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• pp.1115-1133
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• 2024

With the rapid development of AI technology, AI systems are increasingly collecting, processing, and utilizing personal information in large quantities. As a result, transparency and accountability of personal information processing by AI systems, ensuring the rights of information subjects, and minimizing the risk of personal information infringement are becoming important issues. However, the existing privacy policy only discloses the personal information processing in general, and there is no privacy policy for AI systems. In order to solve these problems, In response to the implementation of the privacy policy evaluation system in accordance with the revision of the Personal Information Protection Act, we propose a new AI system privacy policy establishment and disclosure for personal in the design, development and operation of AI system. This study is expected to play a complementary role to the regulations on the right of data subjects to request an explanation and exercise the right of refusal for automated decisions under the current Personal Information Protection Act.

• The Research Journal of the Costume Culture
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• v.26 no.3
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• pp.346-359
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• 2018

Currently, dramatic change had led to the growth of the distribution environment and the retailer's distribution channel. This change had shifted the 'single channel' to 'multi channel', and from 'cross channel' to 'omni channel'. While fashion companies using omni channel are rapidly growing, few research regarding omni channel had been done in academic field. In this study, we examined the influence of omni channel characteristics on consumers' perceived risk as well as consumers' perceived risk toward attitude and intention to use omni channel. We surveyed 696 male and female respondents aged 20 to 40 who lived in Seoul and the metropolitan area. Using AMOS 20.0, factor analysis, reliability analysis, and structural equation model analysis were performed to verify the model of this study. The results were as follows. First, omni channel's instant connectivity, location-based provability, interactivity, and entertainment factors did not decrease impacts on the perceived risk related to privacy and annoyance. Second, omni channel's instant connectivity and entertainment did not increase effects on the perceived financial risk, and location-based provability and interactivity did not increase effect on perceived financial risk. Third, the perceived risk concerning omni channel did not decrease on consumer attitude toward omni channel. Fourth, consumer attitude toward omni channel influenced the intention to use omni channel significantly.

• Journal of the Korean Home Economics Association
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• v.40 no.12
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• pp.49-61
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• 2002

The purpose of this study was to investigate the effect of clothing involvement on the perceived risk in internet shopping and store selection criteria. The subjects used for the study were 210 male and 338 female college students. The clothing involvement consisted of pleasure, symbolism, and selection difficulty factors. The perceived risk consisted of size/defect risk, social psychological risk, privacy risk, delivery risk, and price risk. The store selection criteria had security/service, entertainment/variety, price/convenience factors. The results showed that consumers were segmented by four groups based on clothing involvement factors: clothing pleasure group, symbolism group, confidence group, and low clothing involvement group. The four segmented groups differed in regard to the perceived risk, store selection criteria, and demographics. For example, clothing pleasure group perceived the size/defect risk and social psychological risk higher than did the other groups. Also, the clothing pleasure group considered entertainment/variety more important and had younger female consumers.

• International Journal of Contents
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• v.15 no.4
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• pp.44-49
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• 2019

This study is designed to examine antecedents and consequences of mobile advertising avoidance. However, to date, research on mobile advertising avoidance has been scarce. Thus, this study makes significant contributions by addressing understudied areas in mobile advertising. Study results show that the perceived mobile advertising risk is positively related to mobile advertising avoidance. This study found that the perceived trust in mobile advertising is negatively linked to mobile advertising avoidance. The study results show that the perceived Internet users' data privacy concerns is positively linked to mobile advertising avoidance. Finally, study results suggest that mobile advertising avoidance is positively linked to intention to delete the ad.

• 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.

• Informatization Policy
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• v.19 no.4
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• pp.63-82
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• 2012

The world's best level of ICT(Information, Communication and Technology) infrastructure has experienced the world's worst level of ICT accident in Korea. The number of major accidents of privacy invasion has been three times larger than the total number of Internet user of Korea. The cause of the severe accident was due to big data environment. As a result, big data environment has become an important policy agenda. This paper has conducted analyzing the accident case of data spill to study policy issues for ICT security from a social science perspective focusing on risk. The results from case analysis are as follows. First, ICT risk can be categorized 'severe, strong, intensive and individual'from the level of both probability and impact. Second, strategy of risk management can be designated 'avoid, transfer, mitigate, accept' by understanding their own culture type of relative group such as 'hierarchy, egalitarianism, fatalism and individualism'. Third, personal data has contained characteristics of big data such like 'volume, velocity, variety' for each risk situation. Therefore, government needs to establish a standing organization responsible for ICT risk policy and management in a new big data era. And the policy for ICT risk management needs to balance in considering 'technology, norms, laws, and market'in big data era.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.1
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• pp.99-106
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• 2012

Numerous private corporations and public institutions are collecting personal information through the diverse methods for the purpose of sales, promotion and civil services, and using personal information for the profits of the organizations and services. However, due to immaturity of the technical, managerial measures and internal control for the collected personal information, the misuse, abuse and the leaks of personal information are emerged as major social issues, and the government also is promoting implementation of the act on the privacy protection by recognizing the importance of the personal information protection. This research describes on the measures to detect the anomaly by analyzing personal information treatment patterns managed by the organizations, and on the measures to coup with the leaks, misuse, and abuse of personal information. Particularly, this research is intended to suggest privacy leakage monitoring system design, which can be managed by making the elements related to personal information leaks to numeric core risk indexes to be measured objectively.

• Journal of Families and Better Life
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• v.25 no.2 s.86
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• pp.123-135
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• 2007

This study investigated the influence of values associated with internet auctions and risks associated with participating in internet auctions. The results of this study were as follows: First, the values associated with internet auctions consisted of hedonic value, information value, and practical value. Among these values, hedonic value was the highest, and information value was the lowest. Second, He risks consisted of functional risk, privacy risk, socio-psychological risk, md financial risk. Among these risks, functional risk was the highest, and socio-psychological risk was the lowest. Results of regression analysis using demographic elements to inspect risk factors revealed sex, age, and income were statistically significant finally, with respect to demographic characteristics and influences of the aforementioned values and risks, the factors influencing participation in internet auctions were sex, age, hedonic value, functional risk and financial risk.

• The Research Journal of the Costume Culture
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• v.10 no.3
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• pp.261-269
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• 2002

The purposes of this study were to investigate component of service quality and to determine significant factors on the service quality and buying intention of internet apparel shopping mall. The data were collected from 212 female adults using questionnaire. Using SPSS package, Cronbach's α, factor analysis, and multiple repression analysis were performed. The results could be summarized as follows. 1. The service quality of internet apparel shopping mall was perceived as reliability, advantage, responsibility, product assortment, tangibles, and rapidness. 2. For perceived risk, privacy risk, economic risk, delivery risk, size risk, and quality risk were investigated. The perceived risk except economic risk and web search ability had an effect on the service quality of internet apparel shopping mall. 3. The most of perceived risk, web search ability, and advantage of the service quality had an effect on the shopping intent of the internet apparel shopping mall. Based on the these results, marketing strategies were suggested.