• Journal of Internet Computing and Services
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• v.7 no.5
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• pp.109-121
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• 2006

In this paper, we suggest lattice based role graph security management model which changes security level in mandatory access control model as well as constraint and role hierarchy systematically in role base access control model. In this model, we solved privilege abuse of senior role that is role graph model's problem, and when produce conflict between privileges, we can keep integrity of information by reseting grade of subject through constraint. Also, we offer strong security function by doing to be controlled by subject's security level as well as privilege inheritance by role hierarchy, Finally, we present the role graph algorithms with logic to disallow roles that contain conflicting privileges.

• Journal of the Korea Society of Computer and Information
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• v.14 no.6
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• pp.91-98
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• 2009

In this paper, this model ensures confidentiality and integrity of mandatory access cotrol policy which based on fuzzy function with importance of information. And it solves authorization abuse problem through role graph creation algorithm and flowing policy that security grade is applied. Because this model composes role hierarchy which bind similar role concept to apply to commercial environment, it has expansile advantage by large scale security system as well as is easy that add new role.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.5
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• pp.450-457
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• 2004

In this research, the automatic synthesis of knowledge models is proposed. which are the basis of the methods using qualitative models adapted widely in fault diagnosis and hazard evaluation of chemical processes. To provide an easy and fast way to construct accurate causal model of the target process, the Role-Behavior modeling method is developed to represent the knowledge of modularized process units. In this modeling method, Fault-Behavior model and Structure-Role model present the relationship of the internal behaviors and faults in the process units and the relationship between process units respectively. Through the multiple modeling techniques, the knowledge is separated into what is independent of process and dependent on process to provide the extensibility and portability in model building, and possibility in the automatic synthesis. By taking advantage of the Role-Behavior Model, an algorithm is proposed to synthesize the plant-wide causal model, Fault-Causality Graph (FCG) from specific Fault-Behavior models of the each unit process, which are derived from generic Fault-Behavior models and Structure-Role model. To validate the proposed modeling method and algorithm, a system for building FCG model is developed on G2, an expert system development tool. Case study such as CSTR with recycle using the developed system showed that the proposed method and algorithm were remarkably effective in synthesizing the causal knowledge models for diagnosis of chemical processes.

• Bulletin of the Korean Mathematical Society
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• v.52 no.3
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• pp.955-962
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• 2015

It has been established that the role played by complete graphs in graph theory is similar to the role Dowling group geometries and Projective geometries play in matroid theory. In this paper, we introduce a notion of H-tree, a class of representable matroids which play a similar role to trees in graph theory. Then we give some properties of H-trees such that when q = 0, then the results reduce to the known properties of trees in graph theory. Finally we give explicit expressions of the characteristic polynomials of H-trees, H-cycles, H-fans and H-wheels.

• Journal of Information Technology Applications and Management
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• v.26 no.1
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• pp.65-75
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• 2019

As the use of semantic web based on XML increases in the field of data management, a lot of studies to extract useful information from the data stored in ontology have been tried based on association rule mining. Ontology data is advantageous in that data can be freely expressed because it has a flexible and scalable structure unlike a conventional database having a predefined structure. On the contrary, it is difficult to find frequent patterns in a uniformized analysis method. The goal of this study is to provide a basis for extracting useful knowledge from ontology by searching for frequently occurring subgraph patterns by applying transaction-based graph mining techniques to ontology schema graph data and instance graph data constituting ontology. In order to overcome the structural limitations of the existing ontology mining, the frequent pattern search methodology in this study uses the methodology used in graph mining to apply the frequent pattern in the graph data structure to the ontology by applying iterative node chunking method. Our suggested methodology will play an important role in knowledge extraction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5731-5754
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• 2019

In this paper, we redesign, implement, and evaluate ShareSafe (Based on SecGraph), an open-source secure graph data sharing/publishing platform. Within ShareSafe, we propose De-anonymization Quantification Module and Recommendation Module. Besides, we model the attackers' background knowledge and evaluate the relation between graph data privacy and the structure of the graph. To the best of our knowledge, ShareSafe is the first platform that enables users to perform data perturbation, utility evaluation, De-A evaluation, and Privacy Quantification. Leveraging ShareSafe, we conduct a more comprehensive and advanced utility and privacy evaluation. The results demonstrate that (1) The risk of privacy leakage of anonymized graph increases with the attackers' background knowledge. (2) For a successful de-anonymization attack, the seed mapping, even relatively small, plays a much more important role than the auxiliary graph. (3) The structure of graph has a fundamental and significant effect on the utility and privacy of the graph. (4) There is no optimal anonymization/de-anonymization algorithm. For different environment, the performance of each algorithm varies from each other.

• International Journal of CAD/CAM
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• v.6 no.1
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• pp.99-104
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• 2006

Engineering graph plays an important role in design and manufacture, such as architecture, machinery, manufacture, military. However, almost no persons consider the security and copyright of two-dimensional engineering graph. A novel method for two-dimensional engineering graph watermark based U system is proposed in this paper. Watermarks generated by this technique can be successfully extracted even after rotation, translation and scaling transform.

• Journal of Korea Multimedia Society
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• v.7 no.11
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• pp.1620-1629
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• 2004

The objectives of access control are to protect computing and communication resources from illegal use, alteration, disclosure and destruction by unauthorized users. Although Biba security model is well suited for protecting the integrity of information, it is considered too restrictive to be an access control model for commercial environments. And, Role-Based Access Control(RBAC) model, a flexible and policy-neutral security model that is being widely accepted in commercial areas, has a possibility for compromising integrity of information. In this paper, We present the role graph model which enhanced flexibility and integrity to management of many access permission. Also, In order to represent those rule and constraints clearly, formal descriptions of role assignment rule and constraints in Z language are also given.

• Journal of the Korean School Mathematics Society
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• v.7 no.2
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• pp.81-97
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• 2004

This paper is a study on the understanding process of「Matrix and Graph」on discrete mathematics using TI-92 calculator. For this purpose, we investigated the understanding process of two middle school students learning the concepts of matrix and graph using TI-92 calculator. In this process, we collected qualitative data using recorder and video camera. Then we categorized these data as follows: students' attitude related to using technology, understanding process of meaning, expression and operation of matrix and graph, mathematical communication, etc. From this, we have the following conclusions: First, students inquired out the meaning and role of matrix by themselves using calculator. We could see that calculator can do the role of good learning partner to them. Second, students realized their own mistakes when they used calculator on the process of learning matrix. So we found that calculator could form the self-leading learning circumstance on learning matrix. Third, calculators reinforce the mathematical communication in learning matrix and graph. That is, calculator could be a good mediator to reinforce mathematical communication between teacher and students, among students on learning matrix and graph.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.67-80
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• 2021

The node embedding technique for learning graph representation plays an important role in obtaining good quality results in graph mining. Until now, representative node embedding techniques have been studied for homogeneous graphs, and thus it is difficult to learn knowledge graphs with unique meanings for each edge. To resolve this problem, the conventional Triple2Vec technique builds an embedding model by learning a triple graph having a node pair and an edge of the knowledge graph as one node. However, the Triple2 Vec embedding model has limitations in improving performance because it calculates the relationship between triple nodes as a simple measure. Therefore, this paper proposes a feature extraction technique based on a graph convolutional neural network to improve the Triple2Vec embedding model. The proposed method extracts the neighborliness vector of the triple graph and learns the relationship between neighboring nodes for each node in the triple graph. We proves that the embedding model applying the proposed method is superior to the existing Triple2Vec model through category classification experiments using DBLP, DBpedia, and IMDB datasets.