• Journal of Internet Computing and Services
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• v.15 no.2
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• pp.73-85
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• 2014

This study analyzed the profile of a Facebook account to examine how personal information is revealed and what kinds of factors influence personal information revelation. Categories of user's profile on Facebook were analyzed and two dimensions were developed; the degree that how much personal information is revealed and the network limits that personal information is accessed. Main variables to determine personal information revelation are Facebook privacy concern and uses for social relationships along with gender, the duration of Facebook use, and average time of use. Data were collected from college students. Factor analysis produced two factors of Facebook privacy concern, Facebook privacy concern with users and Facebook privacy concern with the Facebook system. Regression analyses were performed to identify significant determinants of the degree of information revelation and the network limits of personal information. The results found out that the degree of personal information revelation is explained by gender, the duration of use, and use for social relationships while the network limit is explained by the duration of use and Facebook privacy concern with users. Worthy of notice is that use for social relationships and Facebook privacy concern with the Facebook system offset each other. The implications of the results are discussed. Additionally and finally the categories of profiles are graphically re-grouped to show how personal information revelation is associated with social relationship generation and maintenance.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.8
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• pp.853-862
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• 2010

As the mobile device and broadband wireless internet such as WiBro, HSDPA is widely spreading, various types of advertisement and services based on personal location information can be provided. However, with convenience supported by these services, it is possible to be increased an invasion of privacy such as personal location and moving pattern. In this paper, we analysis an essential element for protection of privacy related on location information in mobile environment and propose location privacy protocol for managing location privacy self-control. And we design and implementation prototype of location privacy self-control system which is able to manage user's location privacy condition oneself using the proposed location privacy protocol.

• International Commerce and Information Review
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• v.6 no.2
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• pp.219-242
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• 2004

This study is conducted to find out whether companies which use electronic commerce for their business are collecting the least personal information. of consumers that are necessary for providing electronic commerce services to consumers. Investigators visited website of 799 electronic commerce companies, and checked out the personal informations of consumers that were asked when they join the site as a member. The collected data were analyzed with frequency, percentage, and cross-tab analysis using SPSS program. Generally most electronic commerces required more personal information of consumers than necessary for providing their services to consumers. These phenomena are partly due to the fact that regulations regarding consumer privacy in electronic commerce are advisory rather than mandatory at present. Therefore, it is suggested that mandatory regulation which makes companies poot their identification within a certain area of their web page has to enforced for the protection of consumer privacy in electronic commerce. And it would be more efficient if consumers are consistently educated about self protection guideline regarding personal information in using electronic commerce in addition to a mandatory regulation.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.56-66
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• 2023

The goal of deep learning is to extract complex features from multidimensional data use the features to create models that connect input and output. Deep learning is a process of learning nonlinear features and functions from complex data, and the user data that is employed to train deep learning models has become the focus of privacy concerns. Companies that collect user's sensitive personal information, such as users' images and voices, own this data for indefinite period of times. Users cannot delete their personal information, and they cannot limit the purposes for which the data is used. The study has designed a deep learning method that employs privacy protection technology that uses distributed collaborative learning so that multiple participants can use neural network models collaboratively without sharing the input datasets. To prevent direct leaks of personal information, participants are not shown the training datasets during the model training process, unlike traditional deep learning so that the personal information in the data can be protected. The study used a method that can selectively share subsets via an optimization algorithm that is based on modified distributed stochastic gradient descent, and the result showed that it was possible to learn with improved learning accuracy while protecting personal information.

• Journal of KIISE
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• v.45 no.1
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• pp.45-52
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• 2018

With the advent of BCI technology in recent years, various BCI products have been released. BCI technology enables brain information to be transmitted directly to a computer, and it will bring a lot of convenience to life. However, there is a problem with information protection. In particular, EEG data can raise issues about personal privacy. Collecting and analyzing big data on EEG reports raises serious concerns about personal information exposure. In this paper, we propose a secure privacy-preserving BCI model in a big data environment. The proposed model could prevent personal identification and protect EEG data in the cloud environment.

• Journal of Korean society of Dental Hygiene
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• v.18 no.4
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• pp.561-570
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• 2018

Objectives: This study explored the perception and practice of privacy protection of some dental hygiene students. Methods: On the basis of survey data from 126 respondents, the correlation between the perception and the practice was analyzed. Also the multiple regression analysis was performed on the variables that affect the practice. Cronbach's ${\alpha}$ of the questionnaire was more than 0.6. The items were scored on 5 points scale or true-false type. Results: The perception of privacy protection was 3.23 points, the law is 0.88 points, and the practice is 3.47 points. The educated students were more perceive than those who did not(p<0.05). The higher the perception, the higher the practice(r=0.230, p<0.01). The practice was influenced by the perception(p<0.05). Conclusions: Dental hygiene students should be educated to perceive and protect the personal and medical information of a patient. Also, an educational institutions need a efforts to protect personal information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2708-2730
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• 2012

The growing concern for the protection of personal information has made it critical to implement effective technologies for privacy and data management. By observing the limitations of existing approaches, we found that there is an urgent need for a flexible, privacy-aware system that is able to meet the privacy preservation needs at both the role levels and the personal levels. We proposed a conceptual system that considered these two requirements: a graph-based, access control model to safeguard patient privacy. We present a case study of the healthcare field in this paper. While our model was tested in the field of healthcare, it is generic and can be adapted to use in other fields. The proof-of-concept demos were also provided with the aim of valuating the efficacy of our system. In the end, based on the hospital scenarios, we present the experimental results to demonstrate the performance of our system, and we also compared those results to existing privacy-aware systems. As a result, we ensured a high quality of medical care service by preserving patient privacy.

• 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.

• Asia pacific journal of information systems
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• v.22 no.1
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• pp.53-77
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• 2012

Financial firms, especially large scaled firms such as KB bank, NH bank, Samsung Card, Hana SK Card, Hyundai Capital, Shinhan Card, etc. should be securely dealing with the personal financial information. Indeed, people have tended to believe that those big financial companies are relatively safer in terms of information security than typical small and medium sized firms in other industries. However, the recent incidents of personal information privacy invasion showed that this may not be true. Financial firms have increased the investment of information protection and security, and they are trying to prevent the information privacy invasion accidents by doing all the necessary efforts. This paper studies how effectively a financial firm will be able to avoid personal financial information privacy invasion that may be deliberately caused by internal staffs. Although there are several literatures relating to information security, to our knowledge, this is the first study to focus on the behavior of internal staffs. The big financial firms are doing variety of information security activities to protect personal information. This study is to confirm what types of such activities actually work well. The primary research model of this paper is based on Theory of Planned Behavior (TPB) that describes the rational choice of human behavior. Also, a variety of activities to protect the personal information of financial firms, especially credit card companies with the most customer information, were modeled by the four-step process Security Action Cycle (SAC) that Straub and Welke (1998) claimed. Through this proposed conceptual research model, we study whether information security activities of each step could suppress personal information abuse. Also, by measuring the morality of internal staffs, we checked whether the act of information privacy invasion caused by internal staff is in fact a serious criminal behavior or just a kind of unethical behavior. In addition, we also checked whether there was the cognition difference of the moral level between internal staffs and the customers. Research subjects were customer call center operators in one of the big credit card company. We have used multiple regression analysis. Our results showed that the punishment of the remedy activities, among the firm's information security activities, had the most obvious effects of preventing the information abuse (or privacy invasion) by internal staff. Somewhat effective tools were the prevention activities that limited the physical accessibility of non-authorities to the system of customers' personal information database. Some examples of the prevention activities are to make the procedure of access rights complex and to enhance security instrument. We also found that 'the unnecessary information searches out of work' as the behavior of information abuse occurred frequently by internal staffs. They perceived these behaviors somewhat minor criminal or just unethical action rather than a serious criminal behavior. Also, there existed the big cognition difference of the moral level between internal staffs and the public (customers). Based on the findings of our research, we should expect that this paper help practically to prevent privacy invasion and to protect personal information properly by raising the effectiveness of information security activities of finance firms. Also, we expect that our suggestions can be utilized to effectively improve personnel management and to cope with internal security threats in the overall information security management system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.6
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• pp.121-134
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• 2009

Consumer-centric marketing business is surely one of the most successful emerging business but it poses a threat to personal privacy. Between the service provider and the user there are many contrary issues to each other. The enterprise asserts that to abuse the privacy data which is anonymous there is not a problem. The individual only will not be able to willingly submit the problem which is latent. Web traffic analysis technology itself doesn't create issues, but this technology when used on data of personal nature might cause concerns. The most criticized ethical issue involving web traffic analysis is the invasion of privacy. So we need to inspect how many and what kind of personal informations being used and if there is any illegal treatment of personal information. In this paper, we inspect the operation of consumer-centric marketing tools such as web log analysis solutions and data gathering services with web browser toolbar. Also we inspect Microsoft explorer-based toolbar application which records and analyzes personal web browsing pattern through reverse engineering technology. Finally, this identified and explored security and privacy requirement issues to develop more reliable solutions. This study is very important for the balanced development with personal privacy protection and web traffic analysis industry.