• Journal of Korea Society of Industrial Information Systems
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• v.27 no.3
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• pp.1-10
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• 2022

With the development of web technology, large amounts of web documents are being produced. This web document contains various spatial texts, and by converting these texts into spatial information, it is the basis for searching for text documents with spatial query. These spatial texts consist of a wide range of areas, including postal codes and local phone numbers, as well as administrative place names and POI names. This paper presents algorithms that can map locations based on spatial text information existing within web documents. Through these algorithms, web documents can be searched for documents describing the region on a map rather than a general web search. In this paper, we demonstrated the presented algorithms are useful by implementing a web geo-text query system.

• Journal of Industrial Convergence
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• v.20 no.5
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• pp.61-68
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• 2022

In recent years, malicious codes are being produced using the developing information and communication technology, and it is insufficient to detect them with the existing detection system. In order to accurately and efficiently detect and respond to such intelligent malicious code, an intelligent detection model is required, and in order to maximize detection performance, it is important to train with the main characteristic information set of the malicious code. In this paper, we proposed a technique for designing an intelligent detection model and generating the data required for model training as a set of key feature information through transformation, dimensionality reduction, and feature selection steps. And based on this, the main characteristic information was classified by malicious code. In addition, based on the classified characteristic information, we derived common characteristic information that can be used to analyze and detect modified or newly emerging malicious codes. Since the proposed detection model detects malicious codes by learning with a limited number of characteristic information, the detection time and response are fast, so damage can be greatly reduced and Although the performance evaluation result value is slightly different depending on the learning algorithm, it was found through evaluation that most malicious codes can be detected.

• KNOM Review
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• v.22 no.1
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• pp.60-67
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• 2019

Graphical Processing Units(GPUs) achieve high performance undertaking from relatively uniformed computation in parallel. The technology related to General Purpose GPU(GPGPU) has been enhanced, which provides concurrent kernel execution of multi and diverse applications at the same time, but it is still limited to support resource sharing or planning. NVIDIA recently introduces Multi-Process Service(MPS), which allows kernels from different applications can be execute concurrently. However, the strength of MPS comes along with the characteristics of applications and the order of their execution. This paper shows the performance analysis of diverse scientific applications in real world. Based on the analysis, we prove that it is important to the identify characteristics of co-run applications, and to schedule multiple applications via profiling to maximize MPS functionality.

• KNOM Review
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• v.22 no.1
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• pp.11-19
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• 2019

As technology develops, the latest security threats on the network applied to users are increasing. By attacking industrial or corporate systems with malicious purposes, hackers cause many social problems such as confidential information leakage, cyber terrorism, infringement of information assets, and financial damage. Due to the complex and diversified threats, the current security personnel alone are not enough to detect and analyze all threats. In particular, the Supervisory Control And Data Acquisition (SCADA) used in industrial infrastructures that collect, analyze, and return static data 24 hours a day, 265 days a year, is very vulnerable to real-time security threats. This paper introduces security information and event management (SIEM), a powerful integrated security management system that can monitor the state of the system in real time and detect security threats. Next, we compare SIEM solutions from various companies with the open source SIEM (OSSIM) from AlienVault, which is distributed as an open source, and present cases using the OSSIM and how to utilize it.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.179-184
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• 2022

With the development of information and communication technology, the production and distribution of digital contents is rapidly increasing, and the distribution of illegally copied contents also increases, causing various problems. In order to prevent illegal distribution of contents, a DRM (Digital Rights Management)-based approach can be used, but in a situation where the contents are already copied and distributed, a method of searching and detecting the duplicated contents is required. In this paper, a duplication detection method based on the contents of video content is proposed. The proposed method divides the video into scene units using the visual rhythm extracted from the video, and hierarchically applies the playback time and color feature values of each divided scene to quickly and efficiently detect duplicate videos in a large database. Through experiments, it was shown that the proposed method can reliably detect various replication modifications.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.38-45
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• 2022

Due to the development of fintech technology, financial transactions using smart phones are being activated. The password for user authentication during financial transactions is entered through the virtual keypad displayed on the screen of the smart phone. When the password is entered, the attacker can find out the password by capturing it with a high-resolution camera or spying over the shoulder. A virtual keypad with security applied to prevent such an attack is difficult to input on a small touch-screen, and there is still a vulnerability in peeping attacks. In this paper, the entire keypad is divided into several groups and displayed on a small screen, touching the group to which the character to be input belongs, and then touching the corresponding character within the group. The proposed method selects the group to which the character to be input belongs, and displays the keypad in the group on a small screen with no more than 10 keypads, so that the size of the keypad can be enlarged more than twice compared to the existing method, and the location is randomly placed, hence location of the touch attacks can be blocked.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.669-670
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• 2020

현재 4차 산업이 진행됨으로써 대부분의 사물들이 자율화 기능이 더해지는 시대가 오고 있다. 자율화 기술이 발전됨으로써 모든 사람들은 삶을 살아가면서 스스로 문제를 해결해 나갈수 있으며 기존의 생활속도보다 빨라지는 것을 느낄수 있을 것이다. 그래서 마트에서도 쇼핑을하면서 소비자들이 어떻게 쇼핑을 할 때 현재의 수준보다 쇼핑의 질이 높아 질지 고안해보았다. 본 과제물은 소비자들이 쇼핑을할 때 보다 편리하게 일을 처리할수도록 스마트 기능을 카트와 카운터에 추가하였다. 카트에 디스플레이와 바코드 스캐너를 부착함으로써 검색을 통해 소비자들이 원하는 물품의 가격, 위치등의 정보를 알아 낼 수 있고 현재 카트에 담긴 물품의 총 가격을 알 수 있다. 또한, 쇼핑을 마치고 계산을할 때 계산 대기줄이 길어지는 불편함을 해소하기위해 자동계산 기능이 있다. 쇼핑을 마친 소비자가 카트를 카운터로 끌고가면 카트에 저장되어 있는 쇼핑정보가 카운터의 디스플레이에 표시되고 카트와 카운터의 정보가 일치한다면 소비자가 카트에 요금을 충전해 스스로 계산을 수행할수 있다. 이런 자동화, 스마트 기능들은 소비자들의 편리함과 시간을 단축시킬수 있을 것이다.

• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.33-43
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• 2022

Labeled graphs are used to represent entities, their relationships, and their structures in real data such as knowledge graphs and protein interactions. With the rapid development of IT and the explosive increase in data, there has been a need for a subgraph matching technology to provide information that the user is interested in. In this paper, we propose an approximate Top-k labeled subgraph matching scheme that considers the semantic similarity of labels and the difference in graph structure. The proposed scheme utilizes a learning model using FastText in order to consider the semantic similarity of a label. In addition, the label similarity graph(LSG) is used for approximate subgraph matching by calculating similarity values between labels in advance. Through the LSG, we can resolve the limitations of the existing schemes that subgraph expansion is possible only if the labels match exactly. It supports structural similarity for a query graph by performing searches up to 2-hop. Based on the similarity value, we provide k subgraph matching results. We conduct various performance evaluations in order to show the superiority of the proposed scheme.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.39-44
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• 2023

With the development of e-learning teaching methods, the demand for blended learning, which combines face-to-face education and e-learning, is increasing, and it shows a learning effect that can replace the existing face-to-face class. Engineering subjects have various learning activities such as practice, so it is not easy to operate them with traditional blended learning. Therefore, a different teaching and learning design is required according to the learning activities required for the subject. In this paper, examples of teaching method design and operation for blended learning in engineering subjects were introduced, and their effects investigated and analyzed. Learning activities were subdivided into theoretical classes, practical classes, quizzes and Q&A, assignments and solutions, and teaching and learning methods such as online videos, LMS utilization, and face-to-face classes were applied according to learning activities. According to the results of the student satisfaction survey, blended learning showed higher satisfaction than pure online and face-to-face classes in engineering subjects, and showed differentiated satisfaction for each learning activity.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.113-120
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• 2024

With the advancement of information and communication technology, we can easily generate various forms of data in our daily lives. To efficiently manage such a large amount of data, systematic classification into categories is essential. For effective search and navigation, data is organized into a tree-like hierarchical structure known as a category tree, which is commonly seen in news websites and Wikipedia. As a result, various techniques have been proposed to classify large volumes of documents into the terminal nodes of category trees. However, document classification methods using category trees face a problem: as the height of the tree increases, the number of terminal nodes multiplies exponentially, which increases the probability of misclassification and ultimately leads to a reduction in classification accuracy. Therefore, in this paper, we propose a new node expansion-based classification algorithm that satisfies the classification accuracy required by the application, while enabling detailed categorization. The proposed method uses a greedy approach to prioritize the expansion of nodes with high classification accuracy, thereby maximizing the overall classification accuracy of the category tree. Experimental results on real data show that the proposed technique provides improved performance over naive methods.