• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2C
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• pp.208-218
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• 2006

In this paper, we introduce the creation methods of attack detection model using data mining technologies that can classify the latest attack types, and can detect the modification of existing attacks as well as the novel attacks. Also, we evaluate comparatively these attack detection models in the view of detection accuracy and detection time. As the important factors for creating detection models, there are data, attribute, and detection algorithm. Thus, we used NetFlow data gathered at the real network, and KDD Cup 1999 data for the experiment in large quantities. And for attribute selection, we used a heuristic method and a theoretical method using decision tree algorithm. We evaluate comparatively detection models using a single supervised/unsupervised data mining approach and a combined supervised data mining approach. As a result, although a combined supervised data mining approach required more modeling time, it had better detection rate. All models using data mining techniques could detect the attacks within 1 second, thus these approaches could prove the real-time detection. Also, our experimental results for anomaly detection showed that our approaches provided the detection possibility for novel attack, and especially SOM model provided the additional information about existing attack that is similar to novel attack.

• Journal of Computing Science and Engineering
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• v.1 no.2
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• pp.177-194
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• 2007

Index selection is one of the most important decisions to take in the physical design of relational data warehouses. Indices reduce significantly the cost of processing complex OLAP queries, but require storage cost and induce maintenance overhead. Two main types of indices are available: mono-attribute indices (e.g., B-tree, bitmap, hash, etc.) and multi-attribute indices (join indices, bitmap join indices). To optimize star join queries characterized by joins between a large fact table and multiple dimension tables and selections on dimension tables, bitmap join indices are well adapted. They require less storage cost due to their binary representation. However, selecting these indices is a difficult task due to the exponential number of candidate attributes to be indexed. Most of approaches for index selection follow two main steps: (1) pruning the search space (i.e., reducing the number of candidate attributes) and (2) selecting indices using the pruned search space. In this paper, we first propose a data mining driven approach to prune the search space of bitmap join index selection problem. As opposed to an existing our technique that only uses frequency of attributes in queries as a pruning metric, our technique uses not only frequencies, but also other parameters such as the size of dimension tables involved in the indexing process, size of each dimension tuple, and page size on disk. We then define a greedy algorithm to select bitmap join indices that minimize processing cost and verify storage constraint. Finally, in order to evaluate the efficiency of our approach, we compare it with some existing techniques.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.33-38
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• 2019

In this paper, we propose a new blockchain technology that could comply with GDPR. The proposed model can prevent illegal access by controlling access to the personal information according to a access policy. For example, it can control access to the information on a role-basis and information validation period. The core mechanism of the proposed model is to encrypt the personal information with public key which is associated with users attributes policy, and then decrypt it with a private key and users attributes based on a Attribute-based Encryption scheme. It can reduce a trusted third-part risk by replacing it with a number of nodes selected from the blockchain. And also the private key is generated in the form of one-time token to improve key management efficiency. We proved the feasibility by simulating the proposed model using the chaincode of the Hyperledger Fabric and evaluate the security.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.95-102
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• 2005

In this paper, we propose a user friendly object-based image retrieval system using the interaction between cortex and hippocampus. Most existing ways of queries in content-based image retrieval rely on query by example or query by sketch. But these methods of queries are not adequate to needs of people's various queries because they are not easy for people to use and restrict. We propose a method of automatic color object extraction using CSB tree map(Color and Spatial based Binary をn map). Extracted objects were transformed to bit stream representing information such as color, size and location by region labelling algorithm and they are learned by the hippocampal neural network using the interplay between cortex and hippocampus. The cells of exciting at peculiar features in brain generate the special sign when people recognize some patterns. The existing neural networks treat each attribute of features evenly. Proposed hippocampal neural network makes an adaptive fast content-based image retrieval system using excitatory learning method that forwards important features to long-term memories and inhibitory teaming method that forwards unimportant features to short-term memories controlled by impression.

• Quality Improvement in Health Care
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• v.8 no.2
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• pp.186-207
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• 2001

Background : This study presented an analysis of healthcare quality indicators using data mining and a development of decision support system for quality improvement. Method : Specifically, important factors influencing the key quality indicators were identified using a decision tree method for data mining based on 8,405 patients who discharged from a medical center during the period between December 1, 2000 and January 31, 2001. In addition, a decision support system was developed to analyze and monitor trends of these quality indicators using a Visual Basic 6.0. Guidelines and tutorial for quality improvement activities were also included in the system. Result : Among 12 selected quality indicators, decision tree analysis was performed for 3 indicators ; unscheduled readmission due to the same or related condition, unscheduled return to intensive care unit, and inpatient mortality which have a volume bigger than 100 cases during the period. The optimum range of target group in healthcare quality indicators were identified from the gain chart. Important influencing factors for these 3 indicators were: diagnosis, attribute of the disease, and age of the patient in unscheduled returns to ICU group ; and length of stay, diagnosis, and belonging department in inpatient mortality group. Conclusion : We developed a decision support system through analysis of healthcare quality indicators and data mining technique which can be effectively implemented for utilization review and quality management in a healthcare organization. In the future, further number of quality indicators should be developed to effectively support a hospital-wide Continuous Quality Improvement activity. Through these endevours, a decision support system can be developed and the newly developed decision support system should be well integrated with the hospital Order Communication System to support concurrent review, utilization review, quality and risk management.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.149-156
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• 2010

As following the development of the USN technology, sensor node used in sensor network has capability of quick data process and storage to support efficient network configuration is enabled. In addition, tree-based structure was transformed to cluster in the construction of sensor network. However, query processing based on existing tree structure could be inefficient under the cluster-based network. In this paper, we suggest energy efficient query processing mechanism using filtering through data attribute classification in cluster-based sensor network. The suggestion mechanism use advantage of cluster-based network so reduce energy of query processing and designed more intelligent query dissemination. And, we prove excellence of energy efficient side with MATLab.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.411-416
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• 2020

Field investigations of forests are carried out by writing measured data by hand, and it is a hassle to reorganize the results after a field survey. In this study, a method using object modeling and augmented reality (AR) was applied in a test forest to increase the efficiency of a field investigations. Using a 3D laser scanner, data on were acquired 387 trees within an area of 1 ha at the study site. The coordinates, height, and diameter were calculated through object extraction and modeling of a tree. The proposed can reduce the time required to acquire data in the field and can be used as basic data for building related systems. In addition, the modeling results of trees and a survey using GNSS and AR techniques can be used check coordinates, labor, and attribute information, such as the chest height diameter of the trees being surveyed in the field. The shortcomings of the survey method could be improved. In the future, the method could greatly improve the efficiency of tree surveys and monitoring by reducing the manpower and time required for field surveys.

• Journal of Korea Multimedia Society
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• v.20 no.6
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• pp.927-934
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• 2017

As the technology of drone develops, the use of drone is increasing, In addition, the types of sensors that are inside of smart phones are becoming various and the accuracy is enhancing day by day. Various of researches are being progressed. Therefore, we need to control drone by using smart phone's sensors. In this paper, we propose the most suitable machine learning model that matches the gyro sensor data with drone's moving. First, we classified drone by it's moving of the gyro sensor value of 4 and 8 degree of freedom. After that, we made it to study machine learning. For the method of machine learning, we applied the One-Rule, Neural Network, Decision Tree, and Navie Bayesian. According to the result of experiment that we designated the value from gyro sensor as the attribute, we had the 97.3 percent of highest accuracy that came out from Naive Bayesian method using 2 attributes in 4 degree of freedom. On and the same, in 8 degree of freedom, Naive Bayesian method using 2 attributes showed the highest accuracy of 93.1 percent.

• Proceedings of the Korea Association of Information Systems Conference
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• 2001.12a
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• pp.64-82
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• 2001

HTML revolutionized the way we specify the appearance of data on the Internet. Today, XML (the eXtensible Markup Language) is changing the way we specify the meaning of data. XML, lets document authors define their own markup tags and attribute names to assign meaning to the data elements in the document. Further, XML elements can be nested and include references to indicate data relationships, as Listing One. Unlike HTML, XML markup tags do not describe how to render the data. Rather, they provide descriptions of data, allowing software to understand the meaning of the data automatically For publishing, instead, XSL, the eXtensible Stylesheet Language as a separate language , is in charge of specifying the presentation of XML documents. The purpose of this study is to discover how to transform your organizations relational data into potential e-commerce, business-to-business, and web application with XML and XSL documents. For this purpose, the literature survey, first of all, was undertaken to understand the basic structures of XML documents. Second, one case implementation was performed to understand how to transform Access 2002 XML Files into HTML with XSLTand VB script. The results come out to be successful, more or less. But the limitations of it still exist. One immediate limitation is that XML documents are essentially tree structure, as dictated by the nesting of elements. However, relational database tables are two dimensional matrix structure. In addition, real-world data often is graph structured-a single data element may be referenced in multiple ways. However, this study is useful for understanding how to convert relational database into XML documents and to publish them using XSL or VB script.

• The Journal of Information Technology
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• v.2 no.2
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• pp.35-49
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• 1999

This papar describes an design and implementation of a rule builder, named SGML DTD(Document Type Definition) Editor conforming to ISO 8879(SGML : Standard Generalized Markup Language). SGML DTD define types of logical structure in documents and it is very hard to managing, operating with general common text editors because of it's complex structures. Therefore, We studied DTD automatic editor and production system, prototype system, direct operations on graphic trees in the environment of windows. It's easy to handle with general users. So, We analyzed the structures of document, and studied about SGML documents operation models. And also described logical structures by tree on Windows.