• 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 the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.323-333
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• 2024

Recently, Syntheic data has been in the spotlight as a technology that can protect personal information while maintaining the patterns and characteristics of actual data. Accordingly, technical and institutional research on synthetic data is actively being conducted, but it is difficult to actively use synthetic data due to the lack of clear standards and guidelines. This study is a preliminary study for quantifying the disclosure risk of synthetic data, and derives a privacy disclosure risk index through statistical methodology and suggests specific application measures to comply with the General Data Protection Regulation(GDPR). It is expected that the disclosure risk and the balance of data utility can be controlled through the privacy disclosure risk index of this study in an open data environment.

• Review of KIISC
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• v.27 no.3
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• pp.27-32
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• 2017

머신러닝을 위주로 하는 인공지능 기술이 여러 분야에서 다양하게 적용되고 있다. 머신러닝 기술은 시험 데이터에 대해 높은 성능을 보였지만, 악의적으로 만들어진 데이터에 대해서는 오동작을 하는 경우가 보고되고 있다. 그 외에도 학습데이터 오염시키기, 학습된 모델 탈취 등 새로운 공격 유형이 보고되고 있다. 기계학습에 사용된 훈련데이터에 대한 보안과 프라이버시 또한 중요한 이슈이다. 인공지능 기술의 개발 및 적용에 있어 이러한 위험성에 대한 고려와 대비가 반드시 필요하다.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.453-462
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• 2019

This study investigates the relationship between controllability, severity, unrealistic optimism and risk perception of risk factors related to location - based SNS services for smartphone users. For this purpose, I surveyed university students who had experience using location - based SNS service. The main results are as follows. First, controllability has a statistically significant effect on unrealistic optimism. Second, Severity had a statistically significant negative impact on unrealistic optimism. Third, Controllability did not have a statistically significant effect on risk perception, Fourth, Severity did not have a statistically significant effect on perceived risk. Fifth, Unrealistic optimism had a statistically significant negative impact on perception of risk. The results of this study will contribute to the prevention of privacy incidents and the protection of smartphone users by using location - based SNS service. On the one hand, future research will need to look at the relationship between unrealistic optimism and risk prevention or coping behavior.

• Journal of Distribution Research
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• v.10 no.2
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• pp.1-26
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• 2005

The purpose of this study is to identify the consumer factors influencing the channel choice in the brokerage transaction. The 14 consumer factors were extracted from the two perspectives: first, the off-line channel is based on the relational benefits offered by the salespeople, second, the on-line stock exchange is a transaction mediated by the internet technology. The results shows that the channel choice is significantly influenced by the 8 out of 14 consumer factors hypothesized: interpersonal orientation, risk-taking tendency, amount of money invested, price consciousness, time length of internet usage, innovativeness, information privacy sensitivity, intrinsic desire for information. And the results of discriminant analysis shows that three consumer factors-risk-taking tendency, time length of internet usage, and information privacy sensitivity-are most valuable in discriminating off-line vs. on-line customers.

• Journal of Digital Convergence
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• v.15 no.10
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• pp.183-191
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• 2017

This study tries to explain the relationships among omni-channel service characteristics, utilitarian/hedonic shopping value, and reuse intention. We derive instant connectivity, localization, consistency, integration, privacy risk as omni-channel service characteristics from previous studies and collect data from 190 omni-channel service users. The major findings are as follows. First, localization, consistency, and privacy risk have a significant effect on utilitarian shopping value but no significant effect on hedonic shopping value. Second, instant connectivity and integration have a positive effect on both utilitarian and hedonic value. Third, utilitarian and hedonic shopping value have a positive effect on reuse intention. This study extends the scope of omni-channel consumer behaviors by focusing on multi-dimensionality of shopping value. The results of this research can provide useful implications for practitioners to build successful strategies on omni-channel service.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.1-12
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• 2019

This study explored the factors affecting the acceptance of public recording in SNS post. Using SPSS 21.0 program and AMOS 21.0 program, major results were derived through exploratory factor analysis, confirmatory factor analysis, correlation analysis, and path analysis. The results are as follows: First, the risk of personal information leakage on SNS posting has a significant negative impact on the attitude toward SNS posting. Second, the security of the SNS posting has a significant effect on the attitude toward the SNS posting. Third, the concern about privacy of SNS posting has a significant negative impact on the attitude toward SNS posting. Fourth, the attitude toward SNS posting has a significant effect on the intention to accept the SNS posting. The above results suggest that the SNS post recording should be able to collect opinions of SNS users from a long-term viewpoint.

• The Korean Society of Law and Medicine
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• v.21 no.3
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• pp.145-178
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• 2020

This paper examines discussions surrounding cognitive liberty, neuro-privacy, and mental integrity from the perspective of Neuro-rights. The right to control one's neurological data entails self-determination of collection and usage of one's data, and the right to object to any way such data may be employed to negatively impact oneself. As innovations in neurotechnologies bear benefits and downsides, a novel concept of the neuro-rights has been suggested to protect individual liberty and rights. In Oct. 2020, the Chilean Senate presented the 'Proyecto de ley sobre neuroderechos' to promote the recognition and protection of neuro-rights. This new bill defines all data obtained from the brain as neuronal data and outlaws the commerce of this data. Neurotechnology, especially when paired with big data and artificial intelligence, has the potential to turn one's neurological state into data. The possibility of inferring one's intent, preferences, personality, memory, emotions, and so on, poses harm to individual liberty and rights. However, the collection and use of neural data may outpace legislative innovation in the near future. Legal protection of neural data and the rights of its subject must be established in a comprehensive way, to adapt to the evolving data economy and technical environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.3
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• pp.665-679
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• 2018

With the development of information and communication technology, especially wireless Internet technology and the spread of smart phones, digital data has increased. As a result, privacy issues which concerns about exposure of personal sensitive information are increasing. In this paper, we analyze the privacy vulnerability of online big data in domestic internet environment, especially focusing on portal service, and propose a measure to evaluate the possibility of privacy violation. For this purpose, we collected about 50 million user posts from the potal service contents and extracted the personal information. we find that potal service user can be identified by the extracted personal information even though the user id is partially anonymized. In addition, we proposed a risk measurement evaluation method that reflects the possibility of personal information linkage between service using partial anonymized ID and personal information exposure level.

• Journal of the Korea Convergence Society
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• v.1 no.1
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• pp.23-29
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• 2010

The various kinds of application is distributed for the Smart phone user recently. There is the advantage that the open source application on Android operating system based Smart phone supports a multi tasking service. Layar, Wikitude, and Sherpa and the other applications using the GPS location information like an a2b etc. were developed in the Smart phone environment. However, the existing Cell-ID based location information can be directly collected by the mobile ISP unit which the mobile carrier installs, the personal privacy problem occurs. Therefore, the personal location information is possible to be exposed publicly without any access control procedure. Therefore, in this research, the self-control mechanism on the GPS location information at the Smart phone is designed and presented. Through this, it is possible to develop diverse applications providing enhanced access control and GPS location management on the Android based Smart Phone.