• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.1019-1026
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• 2012

This paper presents a method for the identification of "edge observations" located on a boundary area constructed by a truncation variable as well as for the identification of outliers and the after fit of multivariate skew $t$-distribution(MST) to asymmetric data. The detection of edge observation is important in data analysis because it provides information on a certain critical area in observation space. The proposed method is applied to an Australian Institute of Sport(AIS) dataset that is well known for asymmetry in data space.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.133-138
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• 2024

In the modern academic research environment, the advancement of digital technology provides researchers with increasingly diverse and rich access to information, but at the same time, the issue of author identification has emerged as a new challenge. The problem of author identification is a major factor that undermines the transparency and accuracy of academic communication, potentially causing confusion in the accurate attribution of research results and the construction of research networks. In response, identifier systems such as the International Standard Name Identifier (ISNI) and Open Researcher and Contributor ID (ORCID) have been introduced, but still face limitations due to low participation by authors and inaccurate entry of information. This study focuses on researching information management methods for identification from the moment author information is first entered into the system, proposing ways to improve the accuracy of author identification and maximize the efficiency of academic information services. Through this, it aims to renew awareness of the issue of author identification within the academic community and present concrete measures that related institutions and researchers can take to solve this problem.

• Journal of Information Technology Services
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• v.9 no.3
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• pp.179-191
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• 2010

Service identification and composition is one of the key characteristics for a successful Service-Oriented Computing, being receiving a lot of attention from researchers in recent years. In the Service-Oriented Analysis, the identification of business services has to be preceded before application services are identified. Most approaches addressing the derivation of business services are based on heuristic methods and human experts. The manual identification of business services is highly expensive and ambiguous task, and it may result in the service design with bad quality because of errors and misconception. Although a few of approaches of automatic service identification are proposed, most of them are in focus on technical architectures and application services. In this paper, we propose a model on the automatic identification of business services by horizontal and vertical service alignment using Enterprise Architecture as an ontology. We verify the effectiveness of the proposed model of business services identification through a case study based on Department of Defense Enterprise Architecture.

• Convergence Security Journal
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• v.19 no.5
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• pp.25-36
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• 2019

With the development of information and communication technology, hospitals that electronically process and manage medical information of patients are increasing. However, if medical information is processed electronically, there is still room for infringing personal information of the patient or medical staff. Accordingly, in 2017, the International Organization for Standardization (ISO) published ISO TS 25237 Health Information - Pseudonymization[1]. In this paper, we examine the re - identification process based on ISO TS 25237, the procedure and the problems of our proposed method. In addition, we propose a new processing scheme that adds a re-identification procedure to our secure differential privacy method [2] by keeping a mapping table between de-identified data sets and original data as ciphertext. The proposed method has proved to satisfy the requirements of ISO TS 25237 trust service providers except for some policy matters.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.1063-1070
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• 2021

The development of IT technology emphasizes the importance of training IT professionals, and the need for education for elementary and secondary education as well as adult education for training technical talent is expanding. In particular, information curriculum will be added as an essential course from the 2015 revised curriculum, and IT technology will be understood in the curriculum for elementary and secondary schools and will be required to develop applicability to solve problems based on understanding. Currently, research is under way to integrate IT technologies to provide new services, and if the use of personal information is required in the process, thorough security for the leakage of personal information is pre-empted. It also prevents the identification of personal information in the process of transmitting data to the outside world. In this paper, we propose a training method for elementary school subjects to understand the non-identification process that occurs in the process of transferring data using pipe games so that they can understand the principles of non-identification and develop applications to solve real-life problems.

• Journal of the Korea Society of Computer and Information
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• v.27 no.6
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• pp.53-63
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• 2022

Recently, as digital transformation due to the COVID-19 pandemic accelerates, data to improve individual quality of life is being used in large quantities, and more reinforced non-identification processing procedures are required to utilize the most valuable personal information among data. In Korea, procedures for de-identification measures are presented through amendments to laws and guidelines, but there is no methodology to measure the level of de-identification in the field due to ambiguous processing standards and subjective risk measurement methods. This paper compares and analyzes the current status of policy and guidelines related to de-identification measures proposed at home and abroad to derive complementary points, suggests a data context-based risk measurement method centered on pseudonymized information processing, and verifies its validity. As a result of verification through Delphi survey and focus group interview (FGI), it was confirmed that the need for the proposed methodology and the validity of the indicators were high.

• The Journal of the Korea Contents Association
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• v.11 no.2
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• pp.385-396
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• 2011

The purpose of this study was to investigate contents identification and brand community identification on the brand community. Analysis was performed for the empirical study where important variables of this framework included attractiveness, similarity, intimacy, information quality, contents identification, and community identification, loyalty. I collected the 184 data through survey and analyzed them. The data were recorded and analyzed using the SPSS 14.0 and LSREL 8.30. The brief findings of the study were as below: Given the finding of the study, users who have contents identification directly don't affect on purchase loyalty. Therefore, company intensifies users' visiting community. Users who consistently visit community have purchase loyalty. Existing studies on online brand community is a study for the identification. This study identified the dimensions of the content attribute of the content identification and brand community identification were examined by questionnaires. Accordingly, the company operating the brand community to provide more useful suggestions.

• The KIPS Transactions:PartC
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• v.11C no.4
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• pp.447-454
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• 2004

This paper proposes unforgeable RFID variable n scheme with efficient identification. The existing schemes on privacy protection are in efficient because a server should execute identification process with all Tag ID's Information in order to identify a certain Tag. Moreover these schemes have the serious problem that an attacker can forge special tags if he can know tag's secret information stored in the server's database. Our scheme Is required only 2 times exponent computation to identify a tag. The proposed scheme is also secure against leakage of tags information stored in a database, because an attacker cannot forge special tag even if he knows secret information of the server(database).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1572-1593
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• 2018

The diversity and fast growth of Internet traffic volume are highly influenced by mobile and computer applications being developed. Moreover, the developed applications are too dynamic to be identified and monitored by network administrators. Several approaches have been proposed to identify network applications, however, are still not robust enough to identify modern applications. This paper proposes both, TSA (Traffic collection, Signature generation and Applications identification) system and a derived algorithm so called CSP (Contiguous Sequential Patterns) to identify applications for management and security in IP networks. The major focus of this paper is the CSP algorithm which is automated in two modules (Signature generation and Applications identification) of the proposed system. The proposed CSP algorithm generates DNA-like unique signatures capable of identifying applications and their individual services. In this paper, we show that the algorithm is suitable for generating efficient signatures to identify applications and application services in high accuracy.

• ETRI Journal
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• v.38 no.1
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• pp.174-184
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• 2016

Information identification with image data by means of low-level visual features has evolved as a challenging research domain. Conventional text-based mapping of image data has been gradually replaced by content-based techniques of image identification. Feature extraction from image content plays a crucial role in facilitating content-based detection processes. In this paper, the authors have proposed four different techniques for multiview feature extraction from images. The efficiency of extracted feature vectors for content-based image classification and retrieval is evaluated by means of fusion-based and data standardization-based techniques. It is observed that the latter surpasses the former. The proposed methods outclass state-of-the-art techniques for content-based image identification and show an average increase in precision of 17.71% and 22.78% for classification and retrieval, respectively. Three public datasets - Wang; Oliva and Torralba (OT-Scene); and Corel - are used for verification purposes. The research findings are statistically validated by conducting a paired t-test.