• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2002.11a
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• pp.385-388
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• 2002

본 논문에서는 기본 데이터베이스의 보안적인 취약점에 대해서 알아보고 보안적인 취약점을 해결할 수 있는 방법으로써 Public Key Certificate와 Attribute Certificate를 이용한 서비스 모델을 제시한다. 즉 Public Key Certificate를 이용해서 인증 강도를 높이고 Attribute Certificate를 이용해서 데이터베이스를 사용하는 사용자들에게 Role 기반 권한을 제공해서 사용자들이 데이터베이스를 사용할 수 있는 권한을 손쉽게 세분화 할 수 있는 방법을 제안한다. 또한 공개키 기반 암호화를 사용해서 사용자가 특정 자료를 암호화해서 데이터베이스에 저장함으로써 비도덕적인 데이터베이스 관리자나 혹은 데이터베이스 시스템 내부의 침입자에 의해서 사용자의 데이터가 유출되는 것을 방지하는 방법을 제안한다.

• Asia pacific journal of information systems
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• v.14 no.3
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• pp.77-92
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• 2004

When humans make decisions, they differentiate classifications of individual attribute variables that affect the decisions according to the importance and pattern of each attribute variables. The present study examines the practicality of the proposed Code Arrangement-Based Reasoning(CABR), which resembles the human's way of reasoning. To this end, we developed a CABR technique that classifies each attribute variable affecting significant impacts on the target variable into a cluster and assigns a code to the cluster. For verifying the proposed technique, both case-based reasoning and CABR were used for the customer continuance judgment problem of an automobile insurance company. Results indicated that the performance of CABR is close to the one of the case-based reasoning. The CABR also shows the possibility of using bio-informatics techniques for organizational data analysis in the future.

• Journal of KIISE:Databases
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• v.37 no.6
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• pp.285-291
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• 2010

In this paper, we propose a new paradigm of weighting methods for naive Bayesian learning. We propose more fine-grained weighting methods, called value weighting method, in the context of naive Bayesian learning. While the current weighting methods assign a weight to an attribute, we assign a weight to an attribute value. We develop new methods, using Kullback-Leibler function, for both value weighting and feature weighting in the context of naive Bayesian. The performance of the proposed methods has been compared with the attribute weighting method and general naive bayesian. The proposed method shows better performance in most of the cases.

• Journal of information and communication convergence engineering
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• v.10 no.4
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• pp.343-348
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• 2012

ZigBee Network is enabling technology for home automation, surveillance and monitoring system. For better secure network environment, secure and robust security model is important. The paper proposes an application, attribute-based proxy re-encryption on ZigBee networks. The method can distribute the authority to designated sensor nodes to decrypt re-encrypted ciphertext with associated attributes. However, a previous method is required to compute complex pairing operations. The high complexity is not suited to low resource device sensor networks, and it does not provide routing security either. To resolve these problems, we present a novel mechanism. The method can reduce overhead by imposing overhead to full function devices and ensure routing paths as well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.6133-6151
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• 2017

The field of periocular biometrics has gained wide attention as an alternative or supplemental means to conventional biometric traits such as the iris or the face. Periocular biometrics provide intermediate resolution between the iris and the face, which enables it to support both. We have developed a periocular recognition system by using uniform Multiscale Local Binary Pattern (uMLBP) and attribute features. The proposed system has been evaluated in terms of major factors that need to be considered on a mobile platform (e.g., distance and facial pose) to assess the feasibility of the use of periocular biometrics on mobile devices. Experimental results showed 98.7% of rank-1 identification accuracy on a subset of the Face Recognition Grand Challenge (FRGC) database, which is the best performance among similar studies.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.377-380
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• 2005

최근 다양한 분야에서 임베디드 소프트웨어의 비중이 증대함에 따라 품질 요구 사항이 증대 하였지만, 현실적인 개발 일정은 점점 줄어들고 있다. 이에 본 논문에서는 임베디드 소프트웨어의 기민한 속성 주도 설계(Agile Attribute-Driven Design)를 체계적으로 적용하기 위한 '통합 분석 기법'을 정의한다. 그리고 이를 통한 기민한 설계 접근법을 제안한다. '통합 분석 기법'은 임베디드 소프트웨어의 특성을 고려한 기능 분석과 동시에 '품질 속성 시나리오'를 분석할 수 있는 기법으로서 고품질의 아키텍처 구축을 목적으로 한다. 또한 본 논문에서는 개미 로봇 구현 사례를 통해 '통합 분석 기법'을 검증하고 효과를 확인한다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.143-146
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• 2004

In a situation that rank order information on attribute weights is captured, two solution approaches are presented. An exact solution approach via interaction with a decision-maker pursues progressive reduction of a set of non-dominated alternatives by narrowing down the feasible attribute weights set. In approximate solution approach, on the other hand, three categories of approximate methods such as surrogate weights method, the dominance value-based decision rules, and three classical decision rules are presented and their efficacies in terms of choice accuracy are evaluated via simulation analysis. The simulation results indicate that a method, which combines an exact solution approach through interactions with the decision-maker and the dominance value-based approach is recommendable in a case that a decision is not made at a single step under imprecisely assessed weights information.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.224-234
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• 2004

An XML document processor should process the XML documents according to their purposes and semantics. It is very hard to automatically generate an XML document processor with DTD, because it does not provide the semantic information. In this paper, we introduce an XML document processor generator and a method for specifying semantics using the object-oriented attribute grammar. The XML document processor generator will reduce costs and efforts in developing XML document processors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2115-2127
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• 2021

Although significant progress has been made in synthesizing visually realistic face images by Generative Adversarial Networks (GANs), there still lacks effective approaches to provide fine-grained control over the generation process for semantic facial attribute editing. In this work, we propose a novel cross channel self-attention based generative adversarial network (CCA-GAN), which weights the importance of multiple channels of features and archives pixel-level feature alignment and conversion, to reduce the impact on irrelevant attributes while editing the target attributes. Evaluation results show that CCA-GAN outperforms state-of-the-art models on the CelebA dataset, reducing Fréchet Inception Distance (FID) and Kernel Inception Distance (KID) by 15~28% and 25~100%, respectively. Furthermore, visualization of generated samples confirms the effect of disentanglement of the proposed model.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04a
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• pp.46-48
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• 2001

속성에 할당된 새로운 조건을 통해 평가를 수행할 때 이미 산출된 부분을 재사용하기 위해서는 새로운 평가방법이 필요하다. 이 논문에서는 평가된 속성 값의 전파를 고려한 최적화 알고리즘을 제안하는 기존 속성 트리의 서브 트리와 새로운 속성 트리의 서브 트리를 비교하여 전파되는 속성 값과 노드가 일치할 경우 기존 속성 트리의 서브 트리를 새로운 속성 트리에서 사용이 가능한 최적화된 알고리즘을 제안하고 평가하였다.