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

• Annual Conference of KIPS
• /
• 2022.05a
• /
• pp.264-267
• /
• 2022

Recently, federated learning (FL) has increased prominence as a viable approach for enhancing user privacy and data security by allowing collaborative multi-party model learning without exchanging sensitive data. Despite this, most present FL systems still depend on a centralized aggregator to generate a global model by gathering all submitted models from users, which could expose user privacy and the risk of various threats from malicious users. To solve these issues, we suggested a safe FL framework that employs differential privacy to counter membership inference attacks during the collaborative FL model training process and empowers blockchain to replace the centralized aggregator server.

• Journal of Convergence for Information Technology
• /
• v.8 no.3
• /
• pp.79-84
• /
• 2018

Cloud services are readily available through a variety of media, attracting a lot of attention from users. However, there are various security damages that abuse the privacy of users who use cloud services, so there is not enough technology to prevent them. In this paper, we propose a protection model to safeguard user's privacy in a cloud environment so as not to illegally exploit user's privacy. The proposed model randomly manages the user's signature to strengthen the role of the middle manager and the cloud server. In the proposed model, the user's privacy information is provided illegally by the cloud server to the user through the security function and the user signature. Also, the signature of the user can be safely used by bundling the random number of the multiplication group and the one-way hash function into the hash chain to protect the user's privacy. As a result of the performance evaluation, the proposed model achieved an average improvement of data processing time of 24.5% compared to the existing model and the efficiency of the proposed model was improved by 13.7% than the existing model because the user's privacy information was group managed.

• Journal of Internet Computing and Services
• /
• v.10 no.2
• /
• pp.29-40
• /
• 2009

The development of information technology such as the internet has brought about rapidly changes the old medical technology, e-Healthcare has been to raise social issue. The e-Healthcare which new turning point of paradigm in the medical information develops the medical policy in Korea and the technology, the prospective of reverse engineering in internet environment is incurring problems such as distribution of critical information and invasion and infringement of privacy, etc. In this research, we suggest the Role Based Access Control System, HPIP-e-Healthcare Privacy Information Protection, for solving above problem. The HPIP is composed 4 mechanisms such as Consolidate User Identity, Hospital Authorization, Medical Record Access Control, Patient Diagnosis and we are also prototyping the HPIP for feasible approach in the real computing environment.

• Human Ecology Research
• /
• v.55 no.2
• /
• pp.205-219
• /
• 2017

This study redefines 'consumer privacy attitude and behavior discrepancy' that occurs in the transaction environment that exists between consumer and provider as 'consumer privacy paradox.' In this study, qualitative research was conducted based on grounded theory. This study explored how consumers react to a privacy paradox as well as looked into how to adapt to the negative and positive results that can be generated by the privacy paradox. 'Consumer privacy paradox' is the same as the existing privacy paradox in that consumers can utilize the resources of personal information to consume and benefit from the market environment. However, it differs from previous studies in that it examines the privacy paradox in terms of consumer influence and consumer experience. The results of the study are as follows. First, a paradigm model of the consumer privacy paradox was derived. Second, consumers used three types of strategies to rationalize themselves or maintain indifference or relief to cope with the consumer privacy paradox. Third, the possibility of damage and the responsibility for privacy protection were the mediators of the consumer privacy paradox. Fourth, the 'result' generated by the consumer privacy paradox showed four types of: non-response, satisfaction, commitment to change, and negative emotional experience. Fifth, there is a difference in strategies to respond to the consumer privacy paradox according to consumer types.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.10
• /
• pp.3438-3457
• /
• 2022

As location-based services (LBS) are widely used in vehicular ad-hoc networks (VANETs), location privacy has become an utmost concern. Spatial cloaking is a popular location privacy protection approach, which uses a cloaking area containing k-1 collaborative vehicles (CVs) to replace the real location of the requested vehicle (RV). However, all CVs are assumed as honest in k-anonymity, and thus giving opportunities for dishonest CVs to submit false location information during the cloaking area construction. Attackers could exploit dishonest CVs' false location information to speculate the real location of RV. To suppress this threat, an edge-assisted Trusted Collaborative Anonymity construction scheme called TCA is proposed with trust mechanism. From the design idea of trusted observations within variable radius r, the trust value is not only utilized to select honest CVs to construct a cloaking area by restricting r's search range but also used to verify false location information from dishonest CVs. In order to obtain the variable radius r of searching CVs, a multiple linear regression model is established based on the privacy level and service quality of RV. By using the above approaches, the trust relationship among vehicles can be predicted, and the most suitable CVs can be selected according to RV's preference, so as to construct the trusted cloaking area. Moreover, to deal with the massive trust value calculation brought by large quantities of LBS requests, edge computing is employed during the trust evaluation. The performance analysis indicates that the malicious response of TCA is only 22% of the collaborative anonymity construction scheme without trust mechanism, and the location privacy leakage is about 32% of the traditional Enhanced Location Privacy Preserving (ELPP) scheme.

• Journal of Computing Science and Engineering
• /
• v.7 no.3
• /
• pp.177-186
• /
• 2013

We briefly review the problem of statistical disclosure control under differential privacy model, which entails a formal and ad omnia privacy guarantee separating the utility of the database and the risk due to individual participation. It has born fruitful results over the past ten years, both in theoretical connections to other fields and in practical applications to real-life datasets. Promises of differential privacy help to relieve concerns of privacy loss, which hinder the release of community-valuable data. This paper covers main ideas behind differential privacy, its interactive versus non-interactive settings, perturbation mechanisms, and typical applications found in recent research.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.26 no.6
• /
• pp.1619-1637
• /
• 2016

With wide distribution of smart phones and development of mobile network, social network service (SNS) is displaying remarkable growth rates. Users build new social relations by sharing their interests, which brings surging growth to the SNS based on the combination between the strength of expanding the place for communication and distribution of smart phones featured with easy portability. This study is designed to understand impact factors of SNS on users in Korea and to conduct empirical research on casual relationship between the factors above and the factors affecting personal information behavior through the privacy protection and self-efficacy. In order to accomplish the objective above, the study presented a research model applied with key variables of the Health Belief Model (HBM) predicting behaviors capable of recognizing and preventing individual diseases in the field of health communication. To perform empirical verification on the research model of this study, a survey was conducted upon college students at N university located in Chungcheongnam-do and K university in rural area, who have experiences using the SNS. Through this survey, a total of 186 samples were collected, and path analysis was performed in order to analyze the relationship between the factors. Based on the findings from the survey, first, variables Perceived probability, Perceived severity, Perceived impairment of the HBM, key factors of personal information protection behavior on the SNS, were found to exhibit negative relationship with self-efficacy, and Perceived probability, Perceived benefit, Perceived impairment were found to exhibit negative relationship with privacy protection. But the above, Perceived severity showed positive relationship with privacy protection, and Perceived benefit and self-efficacy also displayed positive relationship. Second, although self-efficacy, a parameter, showed positive relationship with privacy protection, it demonstrated negative relationship with personal information protection behavior. Lastly, privacy protection exhibited positive relationship with personal information protection behavior. By presenting theoretical model reflected with characteristics of prevention based on these findings above unlike previous studies on personal information protection using technologies threatening personal information, this study is to provide theoretical and operational foundation capable of offering explanations how to predict personal information protection behavior on the SNS in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.14 no.1
• /
• pp.189-193
• /
• 2014

SNS (Social Network Service) has evolved to life-friendly service with the combination of local services. Unlike exsiting mobile services, life-friendly service is expected to be personalized with gathering of local information, location information and social network service information. In the process of gathering various kinds of information, Big-data technology and Cloud technology is needed. The effective algorithem has researched for this already, however the privacy protection model hasn't researched enough in life-friendly service or big-data using circumstance. In this paper, the privacy issue is dealt with in terms of 'Structure hole', and the privacy issue comes from big-data technology of life-friendly service.

• Journal of the Korean Data and Information Science Society
• /
• v.13 no.1
• /
• pp.79-86
• /
• 2002

Recently, it is shown that the unrelated quest ion randomized response models proposed by Moors (1971), Folsom et al.(1973), Greenberg et al.(1971) are in capable of protecting the privacy of the respondent. Thus, in this paper, we review recent days research tendency. Also modification model of Mahmood et al.(1998) is proposed, and we show th at this model is more efficient than Greenberg et al.(1969). Furthermore we treat the privacy protection based on Lanke's (1975) risk of suspicion measure.