• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1935-1950
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• 2023

The arrival of the Internet of Things and 5G technology enables users to rely on edge computing platforms to process massive data. Data sharing based on edge computing refines the efficiency of data collection and analysis, saves the communication cost of data transmission back and forth, but also causes the privacy leakage of a lot of user data. Based on attribute-based encryption and blockchain technology, we design a fine-grained access control scheme for data in edge computing, which has the characteristics of verifiability, support for outsourcing decryption and user attribute revocation. User attributes are authorized by multi-attribute authorization, and the calculation of outsourcing decryption in attribute encryption is completed by edge server, which reduces the computing cost of end users. Meanwhile, We implemented the user's attribute revocation process through the dual encryption process of attribute authority and blockchain. Compared with other schemes, our scheme can manage users' attributes more flexibly. Blockchain technology also ensures the verifiability in the process of outsourcing decryption, which reduces the space occupied by ciphertext compared with other schemes. Meanwhile, the user attribute revocation scheme realizes the dynamic management of user attribute and protects the privacy of user attribute.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.879-894
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• 2003

We evaluated the efficiencies of applying attribute selection methods and prior discretization to supervised learning, modelled by C4.5 and Naive Bayes. Three databases were obtained from UCI data archive, which consisted of continuous attributes except for one decision attribute. Four methods were used for attribute selection : MDI, ReliefF, Gain Ratio and Consistency-based method. MDI and ReliefF can be used for both continuous and discrete attributes, but the other two methods can be used only for discrete attributes. Discretization was performed using the Fayyad and Irani method. To investigate the effect of noise included in the database, noises were introduced into the data sets up to the extents of 10 or 20%, and then the data, including those either containing the noises or not, were processed through the steps of attribute selection, discretization and classification. The results of this study indicate that classification of the data based on selected attributes yields higher accuracy than in the case of classifying the full data set, and prior discretization does not lower the accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.145-164
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• 2023

Cloud computing offers a platform that is both adaptable and scalable, making it ideal for outsourcing data for sharing. Various organizations outsource their data on cloud storage servers for availing management and sharing services. When the organizations outsource the data, they lose direct control on the data. This raises the privacy and security concerns. Cryptographic encryption methods can secure the data from the intruders as well as cloud service providers. Data owners may also specify access control policies such that only the users, who satisfy the policies, can access the data. Attribute based access control techniques are more suitable for the cloud environment as they cover large number of users coming from various domains. Multi-authority attribute-based encryption (MA-ABE) technique is one of the propitious attribute based access control technique, which allows data owner to enforce access policies on encrypted data. The main aim of this paper is to comprehensively survey various state-of-the-art MA-ABE schemes to explore different features such as attribute and key management techniques, access policy structure and its expressiveness, revocation of access rights, policy updating techniques, privacy preservation techniques, fast decryption and computation outsourcing, proxy re-encryption etc. Moreover, the paper presents feature-wise comparison of all the pertinent schemes in the field. Finally, some research challenges and directions are summarized that need to be addressed in near future.

• Korean Journal of Human Ecology
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• v.13 no.6
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• pp.943-957
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• 2004

The purpose of this study is to 1) understand the importance of brands, which are known as one of the key purchasing points to consumers today; 2) 10 clearly clarify the various attributes of goods well-known to consumers; 3) to research the effect of the goods attributes on brand attitude. We examined 465 consumers to understand a purchase or a shopping habit with national and non-brand. The study used SPSS 11.0 package for a data analysis. Then using varimax rotation, we employed a factor analysis to analyze the data and obtain Cronbach ${\alpha}$ value. For more specific data analysis, we conducted t-test, regression analysis, and x2 analysis. The results are as followings: 1. The goods attribute is classified into product attribute, shop attribute, and price attribute. The product attribute is divided into wearability, labeling of size and quality, aesthetic expression, brand expression-harmony, textile-suitability, manageability and product assortment. The shop attribute is into shop environment, shopping convenience, promotion, salesperson service, convenience of location, shop's reputation. The price attribute is into price reasonability, price value, price economy, and price information. 2. The product attribute is different, by national and non-brands, in wearability, labeling of size and quality, brand expression-harmony, textile-suitability, manageability. The shop attribute had a significant difference in environment of shop and its reputation, and the price attribute had one only in price economy. 3. The brand attitude was affected by wearability, aesthetic expression, shop environment, price value, and price information. 4. Also, there exists a difference by demographic variables(age, job, academic background, marriage, income level) in brand attitude. For example, national brands have its consumers with the following variables: higher education, higher income, professional job, over 20s, and married.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.34
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• pp.1-8
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• 1995

The practical problem of multi-attribute decision making are formed by the uncertain attribute that the attribute by the alternatives cannot be defined or judged crisphy but only as vague. In this case the final judgements are also represented by vague which have to be ordered to determine the optimal alternative. The problem is more complex if the evaluations of alternatives according to each attribute are expresed vague. This paper described the results of a study done to determine how well multi-attribute decision marking perform in helping a decision maker arrive at a preferred solution to a multi-attribute problem with vague attribute. Particular area of research has concentrated on the issue of combining quantitative and qualitative data supplied by estimation. Futher study considers some method for suitable evaluation of qualitative data.

• Journal of Cadastre & Land InformatiX
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• v.53 no.2
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• pp.107-122
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• 2023

The demand for spatial information in the era of the 4th Industrial Revolution is expanding Additionally, interest in attribute data related to geography or location is increasing. In the field of spatial information, spatial information policies and services tailored to the public can be provided through linkage and integration with new attribute data, and these data are resources for this purpose. In order to meet this expanding and diverse demand for spatial information utilization, it is necessary to develop technologies for linking and utilizing various attribute information such as public data. In this study, we aim to present a technology development strategy for linking and integrating attribute data and spatial information through a review of theories related to data linkage and integration, the current status of data on public data portals, and existing prior research. As a result, it was suggested that the data identifier of the attribute data to be linked should be used to develop linkage technology between spatial information and attribute data, and an attribute data linkage process that can be used when designing a prototype for technology development was presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2292-2309
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• 2017

Ciphertext policy attribute-based encryption (CP-ABE) is a useful cryptographic technology for guaranteeing data confidentiality but also fine-grained access control. Typically, CP-ABE can be divided into two classes: small universe with polynomial attribute space and large universe with unbounded attribute space. Since the learning with errors over rings (R-LWE) assumption has characteristics of simple algebraic structure and simple calculations, based on R-LWE, we propose a small universe CP-ABE scheme to improve the efficiency of the scheme proposed by Zhang et al. (AsiaCCS 2012). On this basis, to achieve unbounded attribute space and improve the expression of attribute, we propose a large universe CP-ABE scheme with the help of a full-rank differences function. In this scheme, all polynomials in the R-LWE can be used as values of an attribute, and these values do not need to be enumerated at the setup phase. Different trapdoors are used to generate secret keys in the key generation and the security proof. Both proposed schemes are selectively secure in the standard model under R-LWE. Comparison with other schemes demonstrates that our schemes are simpler and more efficient. R-LWE can obtain greater efficiency, and unbounded attribute space means more flexibility, so our research is suitable in practices.

• Journal of information and communication convergence engineering
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• v.17 no.2
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• pp.135-141
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• 2019

Collaborative filtering algorithms often encounter data sparsity issues. To overcome this issue, auxiliary information of relevant items is analyzed and an item attribute matrix is derived. In this study, we combine the user-item attribute preference with the traditional similarity calculation method to develop an improved similarity calculation approach and use weights to control the importance of these two elements. A collaborative filtering algorithm based on user-item attribute preference is proposed. The experimental results show that the performance of the recommender system is the most optimal when the weight of traditional similarity is equal to that of user-item attribute preference similarity. Although the rating-matrix is sparse, better recommendation results can be obtained by adding a suitable proportion of user-item attribute preference similarity. Moreover, the mean absolute error of the proposed approach is less than that of two traditional collaborative filtering algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.323-342
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• 2021

Personal health records (PHRs) is an electronic medical system that enables patients to acquire, manage and share their health data. Nevertheless, data confidentiality and user privacy in PHRs have not been handled completely. As a fine-grained access control over health data, ciphertext-policy attribute-based encryption (CP-ABE) has an ability to guarantee data confidentiality. However, existing CP-ABE solutions for PHRs are facing some new challenges in access control, such as policy privacy disclosure and dynamic policy update. In terms of addressing these problems, we propose a privacy protection and dynamic share system (PPADS) based on CP-ABE for PHRs, which supports full policy hiding and flexible access control. In the system, attribute information of access policy is fully hidden by attribute bloom filter. Moreover, data user produces a transforming key for the PHRs Cloud to change access policy dynamically. Furthermore, relied on security analysis, PPADS is selectively secure under standard model. Finally, the performance comparisons and simulation results demonstrate that PPADS is suitable for PHRs.

• Journal of Fisheries and Marine Sciences Education
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• v.29 no.2
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• pp.526-536
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• 2017

This study intended to understand similarity of image between games and position of image attribute perceived by consumers according to the games of marine sports using MDS (Multidimensional Scaling). Through the foregoing, this study aims to provide preliminary data for establishing marketing strategies for games of marine sports by accurately understanding images of marines sports perceived by consumers. For survey targets, this study selected students of K University located in Gyeonggi-do as a population, and extracted samples using convenience sampling out of non-probability sampling methods targeting 200 students who showed intention of participation in this study, and total 188 sheets of questionnaire were used as final data excepting 12 sheets that are filled up unfaithfully or considered unreliable. For data processing, this study conducted Frequency Analysis, Descriptive Statistical Analysis, Reliability Analysis, MDS (Multidimensional Scaling) and Multiple Regression Analysis, and study results show that water ski and wakeboard(.602) have the most similar image attribute, indicating that image attributes of scuba diving and water ski(2.031) are positioned farthest with each other. As for image attribute, image attribute of water ski has appearance and progressiveness, windsurfing has an image attribute of positive, scuba diving has an image attribute of negation, and marin rafting has an image attribute of friendliness.