• 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.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.787-790
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• 1998

In this paper we consider strongly polynomial variations of the auction algorithm for the single origin/all destinations shortest path problem. These variations are based on the idea of graph reduction, that is, deleting unnecessary arcs of the graph by using certain bounds naturally obtained in the course of the algorithm. We study the structure of the reduced graph and we exploit this structure to obtain algorithm with O(n min{m, nlogn}) and O(n$^{2}$) running time.

• The Journal of Korean Association of Computer Education
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• v.6 no.4
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• pp.61-69
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• 2003

RG(Railway Graph), which is a connected graph structure with the concepts of internal and external edges, is a data structure for representing railway assignments in a track network. In RG, it is possible to represent railway connectivities considering it's forward direction which is impossible in a digraph representation. But with RC, we can not still represent an othogonoal railway crossing in a track network. In this paper, we extend RG using the concept of dummy edge. Using ERG(Extended Railway Graph), we describe a method to consistently represent track network including othogonoal railway crossings, data structure for our ERG, and path allocation algorithm in ERG.

• Proceedings of KOSOMES biannual meeting
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• 2007.05a
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• pp.133-139
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• 2007

This paper aims to Analysis on Structure about Information assistance of VTS(vessel traffic service) using fuzzy structure model. Generally, fuzzy structure model is difficult to all structure of a system by difficulty of the choice of critical value and Parameter. In this paper, is able to analysis all structure about information assistance of ITS system by hierarchical structure graph and division graph. Also, this paper is analysis and show a practical problem with interpretation of a model through how some example again.

• Journal of Information Technology Applications and Management
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• v.10 no.4
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• pp.103-118
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• 2003

This study presents a database quality evaluation framework. As a way to build a framework, this study expands data quality management to include data transformation processes as well as data. Further, an information structure graph is applied to represent data transformations processes. An information structure graph is absed on a relational database scheme. Thus, data transformation processes may be stored in a relational database. This kind of integration of data transformation metadata with technical metadata eases evaluation of database qualities and their causes.

• Journal of applied mathematics & informatics
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• v.27 no.3_4
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• pp.531-539
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• 2009

In this paper we first present a structure theorem for an infinite locally finite 3-connected VAP-free planar graph, and in connection with this result we study a possible classification of infinite locally finite planar graphs by reducing modulo finiteness.

• Journal of Communications and Networks
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• v.15 no.4
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• pp.407-410
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• 2013

Secret sharing is that a dealer distributes a piece of information (called a share) about a secret to each participant such that authorized subsets of participants can reconstruct the secret but unauthorized subsets of participants cannot determine the secret. In this paper, an access structure can be represented by a label graph G, where a vertex denotes a participant and a complete subgraph of G corresponds to a minimal authorized subset. The vertices of G are labeled into distinct vectors uniquely determined by the maximum prohibited structure. Based on such a label graph, a verifiable secret sharing scheme realizing general access structures is proposed. A major advantage of this scheme is that it applies to any access structure, rather than only structures representable as previous graphs, i.e., the access structures of rank two. Furthermore, verifiability of the proposed scheme can resist possible internal attack performed by malicious participants, who want to obtain additional shares or provide a fake share to other participants.

• Journal of The Korea Institute of Healthcare Architecture
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• v.21 no.3
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• pp.25-35
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• 2015

Purpose: Signs that are installed at unnoticeable places or that disconnect before the destination can bring errors of location information delivery. Therefore, this study aims to find out the spatial relation between structure of space and signs in the perspective of visual exposure possibility, operating arrangement and assesment by applying spatial structure theory. Methods: Effectiveness of organization of guidance signs was evaluated after the four way-finding factors(Plan Configuration, Sign System, Perceptual Access, Architectural Difference) that G.D.Weisman suggested were interpreted by spatial structure theory(J-Graph analysis, Space Syntax, Visual Graph Analysis) under the premise that it is closely related to the structure of space. Results: 1) Because the south corridor that connects each department of outpatient division is located in the hierarchy center of the space, and walking density is expected to be high, guidance signs need to be organized at the place with high integration value. 2) The depth to the destination space can be estimated through J-Graph analysis. The depth means a switch of direction, and the guidance signs are needed according to the number. 3) According to visibility graph analysis, visual exposure can be different in the same hierarchy unit space according to the shape of the flat surface. Based on these data, location adjustment of signs is possible, and the improvement effect can be estimated quantitatively. Implications: Spatial structure theory can be utilized to design and evaluate sign systems, and it helps to clearly understand the improvement effect. It is desirable to specify design and estimation of sign systems in the order of J-Graph analysis${\rightarrow}$Space Syntax Theory${\rightarrow}$visibility graph analysis.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.649-654
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• 2023

This paper proposes the design of a neural network structure search model using graph convolutional neural networks. Deep learning has a problem of not being able to verify whether the designed model has a structure with optimized performance due to the nature of learning as a black box. The neural network structure search model is composed of a recurrent neural network that creates a model and a convolutional neural network that is the generated network. Conventional neural network structure search models use recurrent neural networks, but in this paper, we propose GC-NAS, which uses graph convolutional neural networks instead of recurrent neural networks to create convolutional neural network models. The proposed GC-NAS uses the Layer Extraction Block to explore depth, and the Hyper Parameter Prediction Block to explore spatial and temporal information (hyper parameters) based on depth information in parallel. Therefore, since the depth information is reflected, the search area is wider, and the purpose of the search area of the model is clear by conducting a parallel search with depth information, so it is judged to be superior in theoretical structure compared to GC-NAS. GC-NAS is expected to solve the problem of the high-dimensional time axis and the range of spatial search of recurrent neural networks in the existing neural network structure search model through the graph convolutional neural network block and graph generation algorithm. In addition, we hope that the GC-NAS proposed in this paper will serve as an opportunity for active research on the application of graph convolutional neural networks to neural network structure search.

• Communications of the Korean Mathematical Society
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• v.11 no.4
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• pp.1159-1174
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• 1996

The spectrum of the Laplacian matrix of a graph gives an information of the structure of the graph. For example, the product of non-zero eigenvalues of the characteristic polynomial of the Laplacian matrix of a graph with n vertices is n times of the number of spanning trees of that graph. The characteristic polynomial of the Laplacian matrix of a graph tells us the number of spanning trees and the connectivity of given graph. in this paper, we compute the characteristic polynomial of the Laplacian matrix of a graph bundle when its voltage lie in an abelian subgroup of the full automorphism group of the fibre; in particular, the automorphism group of the fibre is abelian. Also we study a relation between the characteristic polynomial of the Laplacian matrix of a graph G and that of the Laplacian matrix of a graph bundle over G. Some applications are also discussed.