• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.193-204
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• 2021

Based on risk-benefit theory, this study examined a structural equation model accounting for the mechanisms through which affective perceptions of AI predicting individuals' support for the government's Ai policies. Four perceived characteristics of AI (i.e., usefulness, entertainment value, privacy concern, threat of human replacement) were investigated in relation to perceived benefits/risks, attitudes toward AI, and AI policy support, based on a nationwide sample of South Korea (N=352). The hypothesized model was well supported by the data: Perceived usefulness was a strong predictor of perceived benefit, which in turn predicted attitude and support. Perceived benefit and attitude played significant roles as mediators. Perceived entertainment value along with perceived usefulness and privacy concern predicted attitude, not perceived benefit. Neither attitude nor support was significantly associated with perceived risk which was predicted by privacy concern. Theoretical and practical implications of the results are discussed.

• The Journal of Bigdata
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• v.9 no.1
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• pp.17-30
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• 2024

This study categorizes the factors that affect the intention to continue using ChatGPT into positive motivational factors (personalization, social influence) and negative motivational factors (privacy concern, perceived risk) and investigates whether they affect the intention to continue using ChatGPT through information trust, performance expectancy, and effort expectancy. To this end, a survey was conducted among 265 adults in their 20s and above who have used ChatGPT service. The results showed that personalization and social influence had a defining effect on information trust, performance expectancy, and effort expectancy. For privacy concern, we found a negative effect of wealth on performance expectations, but not on effort expectations. Perceived risk had a negative effect on performance expectancy and effort expectancy. In addition, information trust, performance expectancy, and effort expectancy have a defining effect on continuance intention. This study extends the scope of existing research that focuses on positive factors, deepens our the understanding of ChatGPT. It also provides useful suggestions for continued use of ChatGPT.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.2
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• pp.501-522
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• 2016

In the digital era, information is a source of value creation. However, the growing importance of knowledge and information also increases risks and threats. When information is leaked, full recovery is difficult, and additional spreading of risk is high because it is easy to accomplish. Especially personal information is the main target due to its availability. Although individuals normally have to consent to the use of their personal information, they often do not know the use of their information. In such a difficult situation, one must exercise self-determination and privacy. Therefore, the goal of this study is to development a privacy literacy level measurement model for the proper exercise of the right to informational self-determination. It will be presented with the concept of privacy literacy index in order to determine the level of knowledge and understanding and practical application skills for individual. Through the index, we going to enhance the selection ability of information subject, and to promote the judgement and the determination capability for the protection and utilization of personal information.

• Journal of Digital Convergence
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• v.17 no.7
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• pp.285-292
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• 2019

With the popularization of PC, SNS and IoT, a lot of data is generated and the amount is increasing exponentially. Artificial neural network learning is a topic that attracts attention in many fields in recent years by using huge amounts of data. Artificial neural network learning has shown tremendous potential in speech recognition and image recognition, and is widely applied to a variety of complex areas such as medical diagnosis, artificial intelligence games, and face recognition. The results of artificial neural networks are accurate enough to surpass real human beings. Despite these many advantages, privacy problems still exist in artificial neural network learning. Learning data for artificial neural network learning includes various information including personal sensitive information, so that privacy can be exposed due to malicious attackers. There is a privacy risk that occurs when an attacker interferes with learning and degrades learning or attacks a model that has completed learning. In this paper, we analyze the attack method of the recently proposed neural network model and its privacy protection method.

• Journal of Korean Academy of Nursing Administration
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• v.15 no.1
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• pp.81-90
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• 2009

Purpose: The purpose of this study was to identify nurses' perceptions on the older adult's dignity, and identify the risk factors that threaten older adult dignity and nurses' experiences of ethically difficult care in nursing homes. Method: Qualitative content analysis was done using an analysis scheme developed by the investigators. The data were collected from 51 nurses in 10 different nursing homes, who have agreed this study. Using a self-completion questionnaire was developed by the authors. The questionnaire which consisted of 3 items about dignity definitions, risk factors, and experiences on ethical dilemma. Results: The scheme consisted of 14 categories and 33 subcategories of the 261 significant statements. The categories of the dignity perception analyzed were respect, social right and equality. The categories of risk factors analyzed were loss of control, abuse, physical restraint, invasion of privacy, decision limitation and staff qualification. The categories of dignity experiences were abuse, physical restraint, invasion of privacy, staff qualification and decision limitation. Conclusions: This study may suggests interpretation for compromised older adult's dignity and provides data to use in the development of the useful guidelines and educational programs for the nurses in nursing homes.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1483-1490
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• 2017

Wearable devices need a host device to be paired with because of connectivity, functionality and ease personalization. There should be frequent update and backup processes between the paired devices even without user's consciousness. Due to pairing process, user-specific data are copied from smartphone and transferred to paired smartwatch. We focus on what happens in smartwatch because of pairing process. We perform an experiment study by observing and extracting data from smartwatch under real world usage phases. With a survey of user awareness on smartwatch regarding security and privacy, moreover, we suggest risk assessment on smartwatch in five levels, particularly considering pairing process based on security and privacy.

• Human Ecology Research
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• v.57 no.1
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• pp.1-13
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• 2019

Internet-based financial services are being increasingly integrated into consumers' daily lives. Internet-only banks have emerged as a powerful tool accelerating financial inclusion. This study investigates the satisfaction and continuous use intention predictors for Internet-only banks. We employed an extended post-acceptance model and used six antecedent factors that included perceived usefulness, perceived ease of use, privacy risk, functional risk, subjective norms, and network externality. All 351 participants used Internet-only banks and were 20-40 years of age. A self-administration online survey was conducted. SPSS 23.0 analyzed the frequency, description, and multiple regression analysis. The results of current study are as follows. The education, perceived usefulness, perceived ease of use, and network externality positively influenced the satisfaction of Internet-only banks. Privacy risk negatively influenced satisfaction with Internet-only banks. Perceived ease of use, subjective norm, network externality, and satisfaction positively influenced the continuous use intention of Internet-only banks. The results of our study provide a better explanation of important factors that could enhance the understanding of satisfaction and continuous use intention for Internet-only banks. Furthermore, this study extends the antecedent variables to the knowledge of financial services and enlarges the understanding of users' post-adoption behaviors.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.4
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• pp.71-84
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• 2019

Various researchers conducted the research on two-factor authentication suitable for wireless sensor networks (WSNs) after Das first proposed two-factor authentication combining the smart card and password. After then, To improve the security of user authentication, elliptic curve cryptography(ECC)-based authentication protocols have been proposed. Jiang et al. proposed a privacy-aware two-factor authentication protocol based on ECC for WSM for resolving various problems of ECC-based authentication protocols. However, Jiang et al.'s protocol has the vulnerabilities on a lack of mutual authentication, a risk of SID modification and a lack of sensor anonymity, and user's ID exposed on sensor node Therefore, this paper proposed security enhanced privacy-aware two-factor authentication protocol for wireless sensor networks to solve the problem of Jiang et al.'s protocol, and security analysis was conducted for the proposed protocol.

• The Journal of Information Systems
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• v.33 no.3
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• pp.1-18
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• 2024

Purpose This study aims to identify the factors that negatively affect the perceived usefulness of ChatGPT and their impact on perceived usefulness. Furthermore, this study aims to investigate whether AI literacy can reduce the degree of influence in the relationship between negative factors and perceived usefulness. Design/methodology/approach In this study, we surveyed users aged 20 or older who have been using ChatGPT for at least 3 months. A total of 191 questionnaires were distributed and collected for analysis. To test the hypotheses, path analysis and multiple group analysis were performed. Findings Privacy, limited comprehension, and hallucination were found to have a negative impact on perceived usefulness, while cost risk had no effect. AI literacy was also found to moderate in the relationships between privacy and perceived usefulness and between limited comprehension and perceived usefulness.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.207-216
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• 2024

As big data was built due to the 4th Industrial Revolution, personalized services increased rapidly. As a result, the amount of personal information collected from online services has increased, and concerns about users' personal information leakage and privacy infringement have increased. Online service providers provide privacy policies to address concerns about privacy infringement of users, but privacy policies are often misused due to the long and complex problem that it is difficult for users to directly identify risk items. Therefore, there is a need for a method that can automatically check whether the privacy policy is safe. However, the safety verification technique of the conventional blacklist and machine learning-based privacy policy has a problem that is difficult to expand or has low accessibility. In this paper, to solve the problem, we propose a safety verification technique for the privacy policy using the GPT-3.5 API, which is a generative artificial intelligence. Classification work can be performed evenin a new environment, and it shows the possibility that the general public without expertise can easily inspect the privacy policy. In the experiment, how accurately the blacklist-based privacy policy and the GPT-based privacy policy classify safe and unsafe sentences and the time spent on classification was measured. According to the experimental results, the proposed technique showed 10.34% higher accuracy on average than the conventional blacklist-based sentence safety verification technique.