• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2258-2276
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• 2019

Resource sharing is one of the main goals achieved by network virtualization technology to enhance network resource utilization and enable resource customization. Though resource sharing can improve network efficiency by accommodating various users in a network, limited infrastructure capacity is still a challenge to ultra-low latency service operators. In this paper, we propose an inter-slice resource borrowing schema based on the device-to-device (D2D) potentiality especially for ultra-low latency transmission in cellular networks. An extended and modified Kuhn-Munkres bipartite matching algorithm is developed to optimally achieve inter-slice resource borrowing. Simulation results show that, proper D2D user matching can be achieved, satisfying ultra-low latency (ULL) users' quality of service (QoS) requirements and resource utilization in various scenarios.

• KEPCO Journal on Electric Power and Energy
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• v.5 no.4
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• pp.349-359
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• 2019

This paper introduces a wind turbine simulation system based on the IEC 61400-25 standard to simulate different kinds of wind turbines. A unified communication protocol was required for monitoring and control of wind turbines, because manufacturers had used their own protocols for their turbines. As a result of such an effort, the international standard IEC 61400-25 was established. To implement the schema of IEC 61400-25, the IEC61850 SCL was modified and applied to the simulation system, which enabled the system to be compatible with heterogeneous wind turbine information models. The developed simulation system can be used for interoperability tests with a new type of wind turbine information model.

• The KIPS Transactions:PartC
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• v.11C no.4
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• pp.455-462
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• 2004

Network attacks are various types with development of internet and are a new types. The existing intrusion detection systems need a lot of efforts and costs in order to detect and respond to unknown or modified attacks because of detection based on signatures of known attacks. In this paper, we present a design and implementation for mining prototype system to predict unknown or modified attacks through network protocol attributes analysis. In order to analyze attributes of network protocols, we use the association rule and the frequent episode. The collected network protocols are storing schema of TCP, UDP, ICMP and integrated type. We are generating rules that can predict the types of network attacks. Our mining prototype in the intrusion detection system aspect is useful for response against new attacks as extra tool.

• Korean Institute of Interior Design Journal
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• v.22 no.5
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• pp.207-215
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• 2013

Due to an increase in the number of large-scale and high rise buildings, the importance of indoor location information has been highlighted. As a result, seamless three-dimensional space information, linked to various indoor and outdoor services is required. The purpose of this study is to develop a system which can edit and operate indoor space information using the IndoorGML(Geography Markup Language). It provides functions such as converting and editing authoring indoor space using the IndoorGML. Based on defined schema which is the IndoorGML international standardization work, we develop the "Editor" and "Viewer" for the IndoorGML. When indoor space is modeled in an authoring tool, a variety of topologies can be created automatically. These are available to be edited and modified. Moreover, the file of model can be saved as IndoorGML, SBM and KML file. These files are viewed by the "Viewer". Indoor LBS(Location Based Service)is served with these principles.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.303-316
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• 2021

Digital content protection has recently become an important requirement in biometrics-based authentication systems due to the challenges involved in designing a feasible and effective user authentication method. Biometric approaches are more effective than traditional methods, and simultaneously, they cannot be considered entirely reliable. This study develops a reliable and trustworthy method for verifying that the owner of the biometric traits is the actual user and not an impostor. Watermarking-based approaches are developed using a combination of a color face image of the user and a mobile equipment identifier (MEID). Employing watermark techniques that cannot be easily removed or destroyed, a blind image watermarking scheme based on fast discrete curvelet transform (FDCuT) and discrete cosine transform (DCT) is proposed. FDCuT is applied to the color face image to obtain various frequency coefficients of the image curvelet decomposition, and for high frequency curvelet coefficients DCT is applied to obtain various frequency coefficients. Furthermore, mid-band frequency coefficients are modified using two uncorrelated noise sequences with the MEID watermark bits to obtain a watermarked image. An analysis is carried out to verify the performance of the proposed schema using conventional performance metrics. Compared with an existing approach, the proposed approach is better able to protect multimedia data from unauthorized access and will effectively prevent anyone other than the actual user from using the identity or images.

• Journal of Computing Science and Engineering
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• v.5 no.3
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• pp.183-196
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• 2011

There has recently been a surge of interest in relational database mining that aims to discover useful patterns across multiple interlinked database relations. It is crucial for a learning algorithm to explore the multiple inter-connected relations so that important attributes are not excluded when mining such relational repositories. However, from a data privacy perspective, it becomes difficult to identify all possible relationships between attributes from the different relations, considering a complex database schema. That is, seemingly harmless attributes may be linked to confidential information, leading to data leaks when building a model. Thus, we are at risk of disclosing unwanted knowledge when publishing the results of a data mining exercise. For instance, consider a financial database classification task to determine whether a loan is considered high risk. Suppose that we are aware that the database contains another confidential attribute, such as income level, that should not be divulged. One may thus choose to eliminate, or distort, the income level from the database to prevent potential privacy leakage. However, even after distortion, a learning model against the modified database may accurately determine the income level values. It follows that the database is still unsafe and may be compromised. This paper demonstrates this potential for privacy leakage in multi-relational classification and illustrates how such potential leaks may be detected. We propose a method to generate a ranked list of subschemas that maintains the predictive performance on the class attribute, while limiting the disclosure risk, and predictive accuracy, of confidential attributes. We illustrate and demonstrate the effectiveness of our method against a financial database and an insurance database.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.1128-1131
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• 2005

The document transformation system is more widely used in order to transform business documents efficiently in diverse organization. In established researches on document transformation systems have been carried mainly focused on XML however, it is not only transformed XML form but also EDI or local form in realistic import and export process. Particularly, in the most completed research relate on document transformation, they used ontology to get rid of non-efficiency in the connection of XML schema by manual. Hence, those researches are lack of features, which are construct and modify the domain ontology automatically and the size wasn't enough to realize itself. In this paper we study development of ontology and basic system, which is critical in intelligent document conversion system. And we develop an ontology with editor can be modified and complemented by users, as well as we make it used in real import and export business process.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.83-94
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• 2004

Recent researches which purport to Integrate distributed information have been concentrated on developing efficient mediator systems that not only provide a high degree of autonomy for local users but also support the flexible integration of required functions for global users. However, there has been little attention on how to evaluate a global query in a mediator. A global query is transformed into a set of its sub-queries and each sub-query is the unit of evaluation in a remote server. Therefore, it is possible to speed up the execution of a global query if the previous results of frequently evaluated sub-queries are materialized in a mediator. Since the Integration schema of a mediator can be incrementally modified and the evaluation frequency of a global query can also be continuously varied, query usage should be carefully monitored to determine the optimized set of materialized sub-queries. Furthermore, as the number of sub-queries increases, the optimization process itself may take too long, so that the optimized set Identified by a long optimization process nay become obsolete due to the recent change of query usage. This paper proposes the adaptive selection of materialized sub-queries such that available storage in a mediator can be highly utilized at any time. In order to differentiate the recent usage of a query from the past, the accumulated usage frequency of a query decays as time goes by.

• Spatial Information Research
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• v.17 no.4
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• pp.469-481
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• 2009

Due to the increasing demands on the efficient use of land and the fast growth of construction technologies, human living space is expanded from on the surface to above and under the surface. By recognizing that the current cadastre system based on 2D was not appropriate to reflect the trend, the researchers are interested in a 3D cadastre. This paper proposed the 3D cadastre data model that is appropriate to protect ownership effectively in Korea. The 3D cadastre data model consists of a 3D cadastre feature model and a 3D cadastre geometry model, and the data are produced by a 3D cadastre data structure. A 3D cadastre feature model is based on 3D rights and features derived from case studies. A 3D cadastre geometry model based on ISO19107 Spatial Schema is modified to be good for 3D cadastre in Korea. A 3D cadastre data structure consists of point, line, polygon and solid primitives. This study finally purposes 1) serving and managing land information effectively, 2) creating rights and displaying ranges about infrastructures above and under surface, 3) serving ubiquitous-based geoinformation, 4) adapting ubiquitous-based GIS to urban development, and 5) regulating relationships between rights of land and registration and management systems.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.31-59
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• 2007

We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.