• Journal of the Korean Statistical Society
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• v.34 no.4
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• pp.297-309
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• 2005

We consider 'efficiency versus privacy-protection' problem concerned with several well-known randomized response (RR) devices to estimate pro­portion of people bearing a stigmatizing characteristic in a community. The literature of RR on respondent's privacy protection discusses only about response specific jeopardy measures. We propose a measure of jeopardy that is independent of the RR offered by the interviewee and recommend it for using as a technical characteristic of the RR device. For ensuring better cooperation from the interviewees this new measure that depends only on the design parameters of the RR devices may be disclosed to the respondents before producing the RR by implementing the randomization device.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.1
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• pp.53-59
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• 2012

As the Privacy Act is in force in Korea, the subject of protection responsibility is increased, and continuous efforts are made to protect privacy in overseas countries, as can be seen by standard drafts related to privacy protection. However, the reality is that a formal privacy manual or guidelines are insufficient to help cope with the rapid changes and privacy leak caused by TGIF(Twitter-Google-iPhone-Facebook) these days, and practical effects cannot be expected, even though measures are taken. This paper propose a standard format for satisfying the ISO/IEC 29101 "Privacy Reference Architecture" and shows an implementation example for equipping with forensic readiness capturing indications of the incident rapidly and coming up with an effective counter measure when privacy information is disclosed.

• ETRI Journal
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• v.43 no.5
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• pp.812-824
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• 2021

Recently, with an increase in Internet usage, users of online social networks (OSNs) have increased. Consequently, privacy leakage has become more serious. However, few studies have investigated the difference between privacy and actual behaviors. In particular, users' desire to change their privacy status is not supported by their privacy literacy. Presenting an accurate measurement of users' privacy status can cultivate the privacy literacy of users. However, the highly interactive nature of interpersonal communication on OSNs has promoted privacy to be viewed as a communal issue. As a large number of redundant users on social networks are unrelated to the user's privacy, existing algorithms are no longer applicable. To solve this problem, we propose a structural similarity measurement method suitable for the characteristics of social networks. The proposed method excludes redundant users and combines the attribute information to measure the privacy status of users. Using this approach, users can intuitively recognize their privacy status on OSNs. Experiments using real data show that our method can effectively and accurately help users improve their privacy disclosures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1717-1732
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• 2015

The widespread use of location-based services (LBSs), which allows untrusted service provider to collect large number of user request records, leads to serious privacy concerns. In response to these issues, a number of LBS privacy protection mechanisms (LPPMs) have been recently proposed. However, the evaluation of these LPPMs usually disregards the background knowledge that the adversary may possess about users' contextual information, which runs the risk of wrongly evaluating users' query privacy. In this paper, we address these issues by proposing a generic formal quantification framework,which comprehensively contemplate the various elements that influence the query privacy of users and explicitly states the knowledge that an adversary might have in the context of query privacy. Moreover, a way to model the adversary's attack on query privacy is proposed, which allows us to show the insufficiency of the existing query privacy metrics, e.g., k-anonymity. Thus we propose two new metrics: entropy anonymity and mutual information anonymity. Lastly, we run a set of experiments on datasets generated by network based generator of moving objects proposed by Thomas Brinkhoff. The results show the effectiveness and efficient of our framework to measure the LPPM.

• Information Systems Review
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• v.18 no.3
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• pp.185-207
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• 2016

This study investigated the relationship between privacy policy awareness and willingness to provide personal information. Online privacy policies published on the Internet aim to build the trust of consumers and reduce their concerns about the provision of providing personal information. This study uses FIP(FIP; Fair Information Practices) principles to measure awareness of privacy policy. The result of the survey indicates significant relationships among awareness of privacy policy of e-commerce websites, privacy trust, and privacy risk. Privacy policy aims to improve transparency of collection and use of personal information. A high level of privacy trust is related to a high level of willingness to provide personal information on an e-commerce website. A low level of privacy risk is related to a high level of willingness to provide personal information on an e-commerce website. This study found that disposition to trust moderates the relationship between privacy policy awareness and privacy trust. This study contributes to further research on the relationships among privacy policy awareness, privacy trust, and privacy risk. The result of this study can be used by companies that aim to build privacy trust and reduce privacy risk.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.4
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• pp.53-68
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• 2008

We study on the practical privacy-preserving techniques by matrix-based randomization approach. We clearly examine the relationship between the two parameters associated with the measure of privacy breach and the condition number of matrix in order to achieve the optimal transition matrix. We propose a simple formula for efficiently calculating the inverse of transition matrix which are needed in the re-construction process of random substitution algorithm, and deduce some useful connections among standard error and another parameters by obtaining condition numbers according to norms of matrix and the expectation and variance of the transformed data. Moreover we give some experimental results about our theoretical expressions by implementing random substitution algorithm.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.89-98
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• 2012

According to the enforcement of Personal Information Protection Act as of September 2011, the laws and regulations for the protection of personal information that were applied only to the certain sectors such as information & communication network, financial institutions, public sector etc. for the time being has been expanded to apply to all public and private sectors to process personal information. In particular, because the public institutions are obliged to be mandatorily conducted of the Privacy Impact Assessment, it will be enforced in earnest for each agency's informationization business that handles personal information. In this paper, I examine the most derived vulnerability and set up the improvement measure to supplement it with the examples of 10 of all the institutions conducting the Privacy Impact Assessment in the year 2011. And, I suggest the measures to be prepared by the institutions to observe the Personal Information Protection Act.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1499-1508
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• 2018

Although fast-growing e-commerce markets gave a lot of companies opportunities to expand their customer bases, it is also the case that there are growing number of cases in which the so-called 'black consumers' cause much damage on many companies. In this study, we will implement and optimize a machine learning model that detects black consumers using customer data from e-commerce store. Using filter method for feature selection and 4 different algorithms for classification, we could get the best-performing machine learning model that detects black consumer with F-measure 0.667 and could also yield improvements in performance which are 11.44% in F-measure, 10.51% in AURC, and 22.87% in TPR.

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

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.5
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• pp.1269-1277
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• 2016

European Union and United States have introduced new Privacy Shield agreement after decision of Court of Justice of the European Union which invalidated Safe Harbor agreement. Privacy Shield agreement contains several clauses to raise the level of personal data protection such as enhanced commitments, stronger enforcement, clear safeguards and transparency obligations, and effective protection of EU citizens' rights with several redress possibilities. This agreement has received positive response as an enhanced measure for personal data protection. This paper examines EU and US discussion history and current situation regarding Privacy Shield and suggests national policy direction such as measures for personal data transborder flow system improvement and international cooperation.