• Journal of Internet Computing and Services
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• v.19 no.5
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• pp.67-75
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• 2018

According to Symantec's Internet Security Threat Report(2018), Internet security threats such as Cryptojackings, Ransomwares, and Mobile malwares are rapidly increasing and diversifying. It means that detection of malwares requires not only the detection accuracy but also versatility. In the past, malware detection technology focused on qualitative performance due to the problems such as encryption and obfuscation. However, nowadays, considering the diversity of malware, versatility is required in detecting various malwares. Additionally the optimization is required in terms of computing power for detecting malware. In this paper, we present Stream Order(SO)-CNN and Incremental Coordinate(IC)-CNN, which are malware detection schemes using CNN(Convolutional Neural Network) that effectively detect intelligent and diversified malwares. The proposed methods visualize each malware binary file onto a fixed sized image. The visualized malware binaries are learned through GoogLeNet to form a deep learning model. Our model detects and classifies malwares. The proposed method reveals better performance than the conventional method.

• Journal of Korean Society of societal Security
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• v.2 no.1
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• pp.81-89
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• 2009

A web-based information management system to share engineering data of truss bridge is developed through construction of standardized database of truss bridge. 3D shape information is stored in database according to AP 203 of STEP, and 3D visualization on the web is implemented by using the web 3D technology that helps users to understand geometrical shape of structures, directly. AP209 is used to store structural analysis information such as finite elements, material properties, and analysis result into relational database. Based on the developed database, a prototype of integrated information management system for truss bridge is developed, and it provides additional information such as specifications and inspection information related with shape object to end users.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.117-127
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• 2020

Recently, proving insurance fraud has become increasingly difficult because it occurs intentionally and secretly via organized and intelligent conspiracy by specialists such as medical personnel, maintenance companies, insurance planners, and insurance subscribers. In the case of car accidents, it is difficult to prove intentions; in particular, an insurance company with no investigation rights has practical limitations in proving the suspicions. This paper aims reveal that the detection of organized and conspired insurance fraud, which had previously been difficult, could be dramatically improved through conspiring insurance fraud detection modeling using social network analysis and visualization of the relation between suspected group entities and by seeking developmental research possibilities of data analysis techniques.

• Journal of Korean Society of Disaster and Security
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• v.7 no.2
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• pp.1-8
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• 2014

Smart Pole Measurement System was constructed with not only the core sensors of a GNSS receiver, a TRS sensor and a soil moisture sensor but supplementary installation of power supply and radio communication for monitoring steep slope sites. Also a data processing software for displacement extraction and visualization was developed. Smart Pole Measurement sensor is composed of a GNSS antenna at the top of the pole, a TRS sensor and a gyro sensor vertical below right of the antenna and a soil moisture sensor at the bottom of the pole. The sensor combination extracts not only ground combination in real time but transltion, slide, settlement and soil moisture content. This measuring/monitoring system which cosists of data receiving part, data collection/transfer part and data processing part was built to exercise their functions and then test measuring/monitoring was conducted by introducing artificial displacement and the results were analyzed to evaluate field applicability.

• Journal of KIISE
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• v.45 no.3
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• pp.294-302
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• 2018

With the emergence of the new service industry due to the development of information and communication technology, cyber space risks such as personal information infringement and industrial confidentiality leakage have diversified, and the security problem has emerged as a critical issue. In this paper, we propose a behavior-based anomaly detection method that is suitable for real-time and large-volume data analysis technology. We show that the proposed detection method is superior to existing signature security countermeasures that are based on large-capacity user log data according to in-company personal information abuse and internal information leakage. As the proposed behavior-based anomaly detection method requires a technique for processing large amounts of data, a real-time search engine is used, called Elasticsearch, which is based on an inverted index. In addition, statistical based frequency analysis and preprocessing were performed for data analysis, and the DBSCAN algorithm, which is a density based clustering method, was applied to classify abnormal data with an example for easy analysis through visualization. Unlike the existing anomaly detection system, the proposed behavior-based anomaly detection technique is promising as it enables anomaly detection analysis without the need to set the threshold value separately, and was proposed from a statistical perspective.

• Korean Security Journal
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• no.60
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• pp.91-111
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• 2019

Violent crimes have increased continuously due to the development of urban society and have become a threatening factor against the residential safety of citizens. The prevention of these crimes is always a major topic in human society and one of the fundamental elements of the quality of life and safety of citizens. In recent years, much attention has been paid to environmental design through the Crime Prevention Through Environmental Design (CPTED) as a preventive measure. Currently, South Korea is promoting the openness and utilization of public data, and crime prevention is one of the fields that can utilize public data actively. This approach to crime prevention utilizing public data will be helpful for the proposal of policies from new viewpoints departing from the general utilization measures of CPTED that improve streetlights and closed-circuit television (CCTV) installations, whose limitations have been pointed out as they are only mechanical surveillance. Thus, this study sets the research scope based on the statistics of the status of five criminal offenses by administrative district in recent years provided by the data portal in Seoul City, the capital of South Korea, as the utilization data and concentrates on the analysis. Based on the analysis results, this study proposes a method to utilize classical music as a new policy for regions where the improvements are most needed. The open-source Python analysis program was employed as the main data analysis and visualization method.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.125-133
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• 2016

In recent years, various crimes such as "random killing' crime continue to rise. Despite the government's crime prevention efforts and crime related researches, crime increases and a different approach is needed. Therefore, this study proposes the alternative for crime prevention by analyzing big data. To achieve this objective, this study was to perform visualization utilizing the histogram, the bubble chart and the hit map and association analysis. To analyze the relationship between crime and some variables, this study analyzed data of Seongnam city, Korea National Police Agency and etc. The results of analysis showed that CCTV will be to reduce the crime rate and security light is not significantly relevant. And the result showed that other types of crime focused by time of the day and day of the week and showed that an increase of the foreigners and crime increase are associated. This study presents a scheme for reducing the crime rate on the basis of this analysis result.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2601-2608
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• 2010

It is difficult to merge text document and to remake use of documents on the most collaborative document authoring system using text document, and also to provide the storage place for saving and keeping documents. It has vulnerable drawbacks about the security though it provides the accessible abilities due to basing it on Web. In this paper, we design and implementation the collaborative document authoring system for XML document to improve a couple of problems on these systems. For these, we based on the DOM to manipulate the modeling object documents and utilized RMI on this system without considering socket communication when it transmits and receives Java objects. We improved the security through processes of authentication. By providing templates and editing functions such as annotation, visualization of document structures, we made easier making collaborative document authoring more than ever.

• Convergence Security Journal
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• v.18 no.1
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• pp.33-42
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• 2018

CFD analysis is an analytical technique that applies a computer to the design and development of products across the entire industry for heat or fluid flow. This technology is used to shorten the development period and reduce costs through computerized simulation. However, the software used for CFD analysis is now required to use expensive foreign software. The Opensource CFD analysis software used in the proposed system has reliability of commercial CFD analysis software and has various user groups. However, for users who have expert knowledge, Opensource CFD software which supports only text interface environment, We have developed an environment that enables the construction of a CFD analysis environment for beginners as well as professionals. In addition, the proposed system supports the pre-processing (design and meshing) environment for CFD analysis and the environment for post-processing (result analysis & visualization), enabling the integrated CFD analysis process in one platform.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.565-573
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• 2012

To investigate the business corruption, the obtainments of the business data such as personnel, manufacture, accounting and distribution etc., is absolutely necessary. Futhermore, the investigator should have the systematic extraction solution from the business data of the enterprise database, because most company manage each business data through the distributed database system, In the general business environment, the database exists in the system with upper layer application and big size file server. Besides, original resource data which input by user are distributed and stored in one or more table following the normalized rule. The earlier researches of the database structure analysis mainly handled the table relation for database's optimization and visualization. But, in the point of the digital forensic, the data, itself analysis is more important than the table relation. This paper suggests the extraction technique from the table relation which already defined in the database. Moreover, by the systematic analysis process based on the domain knowledge, analyzes the original business data structure stored in the database and proposes the solution to extract table which is related incident.