• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3497-3515
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• 2018

Differential privacy has broadly applied to statistical analysis, and its mainly objective is to ensure the tradeoff between the utility of noise data and the privacy preserving of individual's sensitive information. However, an individual could not achieve expected data utility under differential privacy mechanisms, since the adding noise is random. To this end, we proposed an adaptive Gaussian mechanism based on expected data utility under conditional filtering noise. Firstly, this paper made conditional filtering for Gaussian mechanism noise. Secondly, we defined the expected data utility according to the absolute value of relative error. Finally, we presented an adaptive Gaussian mechanism by combining expected data utility with conditional filtering noise. Through comparative analysis, the adaptive Gaussian mechanism satisfies differential privacy and achieves expected data utility for giving any privacy budget. Furthermore, our scheme is easy extend to engineering implementation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2778-2791
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• 2017

In the age of big data, distributed data providers need to ensure the privacy, while data analysts need to mine the value of data. Therefore, how to find the privacy-utility tradeoff has become a research hotspot. Besides, the adversary may have the background knowledge of the data source. Therefore, it is significant to solve the privacy-utility tradeoff problem in the distributed environment with side information. This paper proposes a distributed privacy-utility tradeoff method using distributed lossy source coding with side information, and quantitatively gives the privacy-utility tradeoff region and Rate-Distortion-Leakage region. Four results are shown in the simulation analysis. The first result is that both the source rate and the privacy leakage decrease with the increase of source distortion. The second result is that the finer relevance between the public data and private data of source, the finer perturbation of source needed to get the same privacy protection. The third result is that the greater the variance of the data source, the slighter distortion is chosen to ensure more data utility. The fourth result is that under the same privacy restriction, the slighter the variance of the side information, the less distortion of data source is chosen to ensure more data utility. Finally, the provided method is compared with current ones from five aspects to show the advantage of our method.

• ETRI Journal
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• v.32 no.5
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• pp.676-686
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• 2010

Mining sequential patterns is an important research issue in data mining and knowledge discovery with broad applications. However, the existing sequential pattern mining approaches consider only binary frequency values of items in sequences and equal importance/significance values of distinct items. Therefore, they are not applicable to actually represent many real-world scenarios. In this paper, we propose a novel framework for mining high-utility sequential patterns for more real-life applicable information extraction from sequence databases with non-binary frequency values of items in sequences and different importance/significance values for distinct items. Moreover, for mining high-utility sequential patterns, we propose two new algorithms: UtilityLevel is a high-utility sequential pattern mining with a level-wise candidate generation approach, and UtilitySpan is a high-utility sequential pattern mining with a pattern growth approach. Extensive performance analyses show that our algorithms are very efficient and scalable for mining high-utility sequential patterns.

• Communications for Statistical Applications and Methods
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• v.16 no.1
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• pp.1-11
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• 2009

When micro data are released to users, record by record data are disclosed and the disclosure risk of respondent's information is inevitable. Statistical disclosure control techniques are statistical tools to reduce the risk of disclosure as well as to increase data utility in case of data release. In this paper, we reviewed the concept of disclosure and disclosure risk as well as statistical disclosure control techniques and then investigated selection strategies of a statistical disclosure control technique related with data utility. The risk-utility frontier map method was illustrated as an example. Finally, we listed some check points at each step when microdata are released.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.2
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• pp.51-62
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• 2018

High utility sequential pattern (HUSP) mining has been considered as an important research topic in data mining. Although some algorithms have been proposed for this topic, they incur the problem of producing a large search space for HUSPs. The tighter utility upper bound of a sequence can prune more unpromising patterns early in the search space. In this paper, we propose a sequence expected utility (SEU) as a new utility upper bound of each sequence, which is the maximum expected utility of a sequence and all its descendant sequences. A sequence utility list for each pattern is used as a new data structure to maintain essential information for mining HUSPs. We devise an algorithm, high sequence utility list-span (HSUL-Span), to identify HUSPs by employing SEU. Experimental results on both synthetic and real datasets from different domains show that HSUL-Span generates considerably less candidate patterns and outperforms other algorithms in terms of execution time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.1028-1046
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• 2022

Genome-wide association studies (GWAS) aim to find the significant genetic variants for common complex disease. However, genotype data has privacy information such as disease status and identity, which make data sharing and research difficult. Differential privacy is widely used in the privacy protection of data sharing. The current differential privacy approach in GWAS pays no attention to raw data but to statistical data, and doesn't achieve equilibrium between utility and privacy, so that data sharing is hindered and it hampers the development of genomics. To share data more securely, we propose a differential privacy preserving approach of data sharing for GWAS, and achieve the equilibrium between privacy and data utility. Firstly, a reasonable disturbance interval for the genotype is calculated based on the expected utility. Secondly, based on the interval, we get the Nash equilibrium point between utility and privacy. Finally, based on the equilibrium point, the original genotype matrix is perturbed with differential privacy, and the corresponding random genotype matrix is obtained. We theoretically and experimentally show that the method satisfies expected privacy protection and utility. This method provides engineering guidance for protecting GWAS data privacy.

• Journal of the Korean Professional Engineers Association
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• v.33 no.4
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• pp.27-32
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• 2000

The automatic utility program in electrical facilities has specially developed to fulfill the needs of electric CAD designers . Designers had separately managed the designing factors such as design, estimates and calculation sheets . However, this automatic utility program produces calculation sheets and volume reports simultaneously while designed. The program also accumulates all data automatically in database in order to be utilized as the statistics and the design data for later project management. Moreover, it is easy for new and inexperienced users to access by using the standard electric symbol libraries and utility modules.

• The Journal of Industrial Distribution & Business
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• v.10 no.1
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• pp.39-49
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• 2019

Purpose - Previous studies examined effects of sharing economy in the fields such as accommodation and automobile sector, while there are lack of researches in the field of skill-sharing economy. By classifying skill-sharing into general and special skill-sharing, this study explored effects of variables such as transaction utility, social utility, sustainability utility, emotional utility, economic utility, and trust utility, on attitudes, intention, satisfaction, and loyalty of demand (i.e., customers) and supply (i.e., providers) sides, potential, and actual customers. Research design, data, and methodology - Data were collected via both online and offline surveys. This study applied factor analysis and multiple regression analysis for findings. Results - Results show that utilities for general suppliers' skill-sharing are significant than other cases. Among utilities, this study found that trust utility shows significant for the cases of special customers', general suppliers' and special suppliers' potential skill-sharing. The results implies that trust is crucial in the transaction of the sharing economy. Conclusions - Enhanced managerial systems help resolve issues on the sharing economy. This study provides implications what are positive effects of skill-sharing economy and recommends proper establishment of the sharing economy.

• Asia Marketing Journal
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• v.16 no.2
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• pp.15-38
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• 2014

This paper explores the influence of pursuing goals on customer channel preference in Chinese rural market. With the rapid change in distribution channels and increase in multi-channels, it is necessary to understand the preference for channel choice as well as product choice. This study empirically validated the conceptual framework of the relationship between the pursuing goals and customer channel choice proposed by Balasubramanian, Raghunathan, and Mahajan (2005). Based on the survey data of 232 fertilizer customers in Chinese rural market, this study explores how economic, social, and psychological pursuing goals can impact customer channel preference by mediating variables of product utility and process utility. The results indicate that pursuing goals positively related with product utility and process utility, and product / process utility can mediate the relationship between pursuing goals and customer channel preference positively. Consequently, we can conclude that customers' economic-social-psychological pursuing goals can directly influence customer channel preference via their purchase process utility and product utility. This result also implies that product utility is effective on process utility during consumer's buying decision making, and process utility and product utility are not mutually independent. Therefore, purchase process utility is a "latent driving force" on customer's channel choice decision.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.69-76
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• 2024

Recent advances in sensor and mobile technologies have made it possible to collect user location data. This location information is used as a valuable asset in various industries, resulting in increased demand for location data collection and sharing. However, because location data contains sensitive user information, indiscriminate collection can lead to privacy issues. Recently, geo-indistinguishability (Geo-I), a method of differential privacy, has been widely used to protect the privacy of location data. While Geo-I is powerful in effectively protecting users' locations, it poses a problem because the utility of the collected location data decreases due to data perturbation. Therefore, this paper proposes a method using Geo-I technology to effectively collect user location data while maintaining its data utility. The proposed method utilizes the prior distribution of users to improve the overall data utility, while protecting accurate location information. Experimental results using real data show that the proposed method significantly improves the usefulness of the collected data compared to existing methods.