• 한국가스학회지
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• 제2권1호
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• pp.53-58
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• 1998

화학공정 변수간의 관계를 표현하는 방법으로, 지식기반 접근법을 이용하여 부호유향그래프(signed directed graph, SDG)를 자동합성하였다. SDG의 자동합성은 지식베이스를 이용한 추론과정 및 Loop 검증의 두 단계를 거쳐 수행된다. 먼저, 공정내 장치를 중심으로 장치간의 결합관계를 Topology로 표현하고, Topology 정보를 이용한 공정 변수관계 표현 및 지식베이스의 공정경향 데이타를 문자 패턴 매칭하여 Primary-SDG를 자동으로 합성한다. 생성된 Primary-SDG를 Loop 검증기의 추론을 통하여 검증, 수정하여 SDG를 자동합성하였다.

• 대한원격탐사학회지
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• 제18권2호
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• pp.107-116
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• 2002

Watershed 알고리듬을 통해 에지 기반과 영역 기반 기법을 결합한 하이브리드 영상 분할 알고리듬을 제안하였다. 먼저 minimax flow와 결합된 평균 곡률 확산을 이용하여 에지를 보존하면서 잡음을 제거를 수행한다. 영상을 watershed 알고리듬을 이용하여 분할한 후에 RAG (Region Adjacency Graph)을 사용하여 분할된 영역들간의 관계를 분석한다. RAG의 그래프 노드와 에지 비용은 분할된 영역과 두 인접한 영역사이의 상이함을 나타낸다. 최소 비용의 RAG의 에지를 찾아 가장 유사한 영역 쌍이 결정되면 두 영역은 서로 합치고 RAG은 갱신된다. 제안한 방법을 통해서 잡음을 효과적으로 감소시키고 한 화소 두께의, 닫힌 경계선을 획득할 수 있었다.

• 한국컴퓨터정보학회논문지
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• 제23권11호
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• pp.75-84
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• 2018

Social engineering attack means to get information of Social engineering attack means to get information of opponent without technical attack or to induce opponent to provide information directly. In particular, social engineering does not approach opponents through technical attacks, so it is difficult to prevent all attacks with high-tech security equipment. Each company plans employee education and social training as a countermeasure to prevent social engineering. However, it is difficult for a security officer to obtain a practical education(training) effect, and it is also difficult to measure it visually. Therefore, to measure the social engineering threat, we use the results of social engineering training result to calculate the risk by system asset and propose a attack graph based probability. The security officer uses the results of social engineering training to analyze the security threats by asset and suggests a framework for quick security response. Through the framework presented in this paper, we measure the qualitative social engineering threats, collect system asset information, and calculate the asset risk to generate probability based attack graphs. As a result, the security officer can graphically monitor the degree of vulnerability of the asset's authority system, asset information and preferences along with social engineering training results. It aims to make it practical for companies to utilize as a key indicator for establishing a systematic security strategy in the enterprise.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권9호
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• pp.3258-3273
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• 2021

Malware is a severe threat to the computing system and there's a long history of the battle between malware detection and anti-detection. Most traditional detection methods are based on static analysis with signature matching and dynamic analysis methods that are focused on sensitive behaviors. However, the usual detections have only limited effect when meeting the development of malware, so that the manual update for feature sets is essential. Besides, most of these methods match target samples with the usual feature database, which ignored the characteristics of the sample itself. In this paper, we propose a new malware detection method that could combine the features of a single sample and the general features of malware. Firstly, a structure of Directed Cyclic Graph (DCG) is adopted to extract features from samples. Then the sensitivity of each API call is computed with Markov Chain. Afterward, the graph is merged with the chain to get the final features. Finally, the detectors based on machine learning or deep learning are devised for identification. To evaluate the effect and robustness of our approach, several experiments were adopted. The results showed that the proposed method had a good performance in most tests, and the approach also had stability with the development and growth of malware.

• 한국전자통신학회논문지
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• 제17권5호
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• pp.801-808
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• 2022

대규모 링크드 데이터에 어떻게 지식을 임베딩하고, 엔티티 매칭을 위해 어떻게 신경망 모델을 적용할 것인가에 대한 연구는 상대적으로 많이 부족한 상황이다. 이에 대한 가장 근본적인 문제는 서로 다른 레이블이 어휘 이질성을 초래한다는 것이다. 본 논문에서는 이러한 어휘 이질성 문제를 해결하기 위해 재정렬 구조를 결합한 확장된 GCN(Graph Convolutional Network) 모델을 제안한다. 제안된 모델은 기존 임베디드 기반 MTransE 및 BootEA 모델과 비교하여 각각 53% 및 40% 성능이 향상되었으며, GCN 기반 RDGCN 모델과 비교하여 성능이 5.1% 향상되었다.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1999년도 춘계학술대회 논문집
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• pp.242-250
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• 1999

The objective of this paper is to propose an Extended AND-OR Graph (EAOG)-driven inferential simulation mechanism with which decision makers engaged in electronic commerce (EC) can effectively deal with complicated decision making problem. In the field of traditional expect systems research, AND-OR Graph approach cannot be effectively used in the EC problems in which real-time problem-solving property should be highly required. In this sense, we propose the EAOG inference mechanism for EC problem-solving in which heurisric knowledge necessary for intelligent EC problem-solving can be represented in a form of matrix. The EAOG method possesses the following three characteristics. 1. Realtime inference: The EAOG inference mechanism is suitable for the real-time inference because its computational mechanism is based on matrix computation.2. Matrix operation: All the subjective knowledge is delineated in a matrix form, so that inference process can proceed based on the matrix operation which is computationally efficient.3. Bi-directional inference: Traditional inference method of expert systems is based on either forward chaining or based on either and computational efficiency. However, the proposed EAOG inference mechanism is generically bi-directional without loss of both speed and efficiency.We have proved the validity of our approach with several propositions and an illustrative EC example.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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• pp.671-674
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• 2000

In this paper, we present a robust global registration algorithm for multi-frame image mosaics. When we perform a pair-wise registration recovering a projective transformation between two consecutive frames, severe mis-registration among multiple frames, which are not consecutive, can be detected. It is because the concatenation of those pair-wise transformations leads to global alignment errors. To overcome those mis-registrations, we propose a new algorithm using multiple frames for constructing image mosaics. We use a graph to represent the temporal and spatial connectivity and show that global registration can be obtained through the search for an optimal path in the constructed graph. The definition of an adequate objective function characterizing the global registration provides a direct manipulation of the graph. In the presence of moving objects, especially large ones compared with low texture backgrounds, by using the likelihood ratio as the objective function, we can deal with some of the most challenging videos like basketball or soccer Moreover, the algorithm can be parallelized so it can be more efficiently implemented. Finally, we give some experimental results from real videos.

• International Journal of Contents
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• 제10권1호
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• pp.23-28
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• 2014

When developing a classifier using various objective functions, it is important to compare the performances of the classifiers. Although there are statistical analyses of objective functions for classifiers, simulation results can provide us with direct comparison results and in this case, a comparison criterion is considerably critical. A Receiver Operating Characteristics (ROC) graph is a simulation technique for comparing classifiers and selecting a better one based on a performance. In this paper, we adopt the ROC graph to compare classifiers trained by mean-squared error, cross-entropy error, classification figure of merit, and the n-th order extension of cross-entropy error functions. After the training of feed-forward neural networks using the CEDAR database, the ROC graphs are plotted to help us identify which objective function is better.

• International Journal of Contents
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• 제10권3호
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• pp.41-46
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• 2014

A cause-effect graph considers only the desired external behavior of a system by identifying input-output parameter relationships in the specification. When testing a software system with cause-effect graphs, it is important to derive a moderate number of tests while avoiding loss in fault detection ability. Pairwise testing is known to be effective in determining errors while considering only a small portion of the input space. In this paper, we present a new testing technique that generates pairwise tests from a cause-effect graph. We use a Boolean Satisbiability (SAT) solver to generate pairwise tests from a cause-effect graph. The Alloy language is used for encoding the cause-effect graphs and its SAT solver is applied to generate the pairwise tests. Using a SAT solver allows us to effectively manage constraints over the input parameters and facilitates the generation of pairwise tests, even in the situations where other techniques fail to satisfy full pairwise coverage.

• 한국콘텐츠학회논문지
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• 제9권2호
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• pp.142-151
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• 2009

기존의 문서 군집화 기법 NSTC은 문서 군집화 과정 내에서 TF-IDF를 이용하여 문서간 유사도를 측정한다. 본 논문에서는 TF-IDF가 아닌, 공통 Phrase의 관계 그래프를 이용한 새로운 문서간 유사도 측정을 제안한다. 이 방법은 문서 집합 내의 공통 Phrase들의 관계를 나타낸 관계 그래프를 통해 공통 Phrase의 가중치를 부여하는 방법을 제시한다. 또한 실험을 통해 NSTC와 비교하여 본 논문에서 제안한 문서간 유사도 측정 기법이 문서 군집화에 더욱 효과적임을 보였다.