• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.605-616
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• 2020

Obfuscation technology delays the analysis of a program by modifying internal logic such as data structure and control flow while maintaining the program's functionality. However, the application of such obfuscation technology to malicious code frequently occurs to reduce the detection rate of malware in antivirus software. The obfuscation technology applied to protect software intellectual property is applied to the malicious code in reverse, which not only lowers the detection rate of the malicious code but also makes it difficult to analyze and thus makes it difficult to identify the functionality of the malicious code. The study of reverse obfuscation techniques that can be closely restored should also continue. This paper analyzes the characteristics of obfuscated code with the option of Pack the Output File and Import Protection among detailed obfuscation technologies provided by VMProtect 3.4.0, a popular tool among commercial obfuscation tools. We present a de-obfuscation algorithm.

• Journal of KIISE:Databases
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• v.35 no.2
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• pp.125-131
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• 2008

It is very useful to predict orthologs for new genome annotation and research on genome evolution. We showed that the previous work can be extended to construct OCs(Ortholog Clusters) automatically from multiple complete-genomes. The proposed method also has the quality of production of InParanoid, which produces orthologs from just two genomes. On the other hand, in order to predict more exactly the function of a newly sequenced gene it can be an important issue to prevent unwanted inclusion of paralogs into the OCs. We have, here, investigated how well it is possible to construct a functionally purer OCs with score cut-offs. Our OCs were generated from the datasets of 20 procaryotes. The similarity with both COG(Clusters of Orthologous Group) and KO(Kegg Orthology) against our OCs has about 90% and inclines to increase with the growth of score cut-offs.

• Journal of the Korean Society of Marine Environment & Safety
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• v.10 no.1 s.20
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• pp.1-7
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• 2004

RADARSAT is one of many possible data sources that can play an important role in marine surveillance including ship detection because radar sensors have the two primary advantages: all-weather and day or night imaging. However, atmospheric effects on SAR imaging can not be bypassed and any remote sensing image has various geometric distortions, In this study, radiometric and geometric calibrations for RADARSAT/SAT data are tried using SGX products georeferenced as level 1. Even comparison of the near vs. far range sections of the same images requires such calibration Radiometric calibration is performed by compensating for effects of local illuminated area and incidence angle on the local backscatter, Conversion method of the pixel DNs to beta nought and sigma nought is also investigated. Finally, automatic geometric calibration based on the 4 pixels from the header file is compared to a marine chart. The errors for latitude and longitude directions are 300m and 260m, respectively. It can be concluded that the error extent is acceptable for an application to open sea and can be calibrated using a ground control point.

• Journal of Convergence Society for SMB
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• v.1 no.1
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• pp.75-83
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• 2011

Unified Modeling Language (UML) is widely accepted in industry and particularly UML State Machine Diagram is popular for describing the dynamic behavior of classes. This paper discusses deadlock detection of System using UML State Machine Diagram. Since a State Machine Diagram is used for indivisual class' behavior, all the State Machine Diagrams of the classes in the system are combined to make a big system-wide State Machine Diagram to describe system behavior. Generally this system-wide State Machine Diagram is very complex and contains invalid state and transitions. To make it a usable and valid State Machine Diagram, synchronization and externalization are applied. The reduced State Machine Diagram can be used for describing system behavior thus conventional model-checking technique can be applied. This paper shows how deadlock detection of system can be applied with simple examples. All the procedures can be automatically done in the tool.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.665-670
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• 2014

A SVM is a kind of binary classifier in order to find optimal hyperplane which separates training data into two groups. Due to its remarkable performance, the SVM is applied in various fields such as inductive inference, binary classification or making predictions. Also it is a representative black box model; there are plenty of actively discussed researches about analyzing trained SVM classifier. This paper conducts a study on a method that is automatically detecting the line-shaped echoes, sun strobe echo and radial interference echo, using the SVM algorithm because the line-shaped echoes appear relatively often and disturb weather forecasting process. Using a spatial clustering method and corrected reflectivity data in the weather radar, the training data is made up with mean reflectivity, size, appearance, centroid altitude and so forth. With actual occurrence cases of the line-shaped echoes, the trained SVM classifier is verified, and analyzed its characteristics using the decision tree method.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.4
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• pp.135-144
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• 2018

The domestic pigsty environment is highly vulnerable to the spread of respiratory diseases such as foot-and-mouth disease because of the small space. In order to manage this issue, a variety of studies have been conducted to automatically analyze behavior of individual pigs in a pig pen through a video surveillance system using a camera. Even though it is required to correctly segment touching pigs for tracking each pig in complex situations such as aggressive behavior, detecting the correct boundaries among touching pigs using Kinect's depth information of lower accuracy is a challenging issue. In this paper, we propose a segmentation method using motion information of the touching pigs. In addition, our proposed method can be applied for detecting tracking errors in case of tracking individual pigs in the complex environment. In the experimental results, we confirmed that the touching pigs in a pig farm were separated with the accuracy of 86%, and also confirmed that the tracking errors were detected accurately.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1099-1108
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• 2009

The study of IP address allocation in MANET can be categories into Stateful and Stateless. The one, special node monitors other nodes' IP address and allocates IF address. And the other, node generates IP address by itself. Nodes in MANET have mobility and restricted resource, so Stateless is more suitable than Stateful. But, in Stateless, node requires DAD process because of unique IP address allocation. And Dos attack can be happened in DAD precess. In this paper, we propose a security method on preventing DoS attack against DAD in MANET using one-way hash function. Since, Computation of one-way hash function is suitable for nodes' restricted resource character in MANET. And we evaluate performance using NS2 and compare with other security method which is CGA using signature.

• Journal of the Korean Geotechnical Society
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• v.34 no.12
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• pp.145-154
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• 2018

The damage investigation and inspection methods performed in concrete facilities such as bridges, tunnels, retaining walls and so on, are usually visually examined by the inspector using the surveying tool in the field. These methods highly depend on the subjectivity of the inspector, which may reduce the objectivity and reliability of the record. Therefore, the new image processing techniques are necessary in order to automatically detect the cracks and objectively analyze the characteristics of cracks. In this study, deep learning and image processing technique were developed to detect cracks and analyze characteristics in images for concrete facilities. Two-stage image processing pipeline was proposed to obtain crack segmentation and its characteristics. The performance of the method was tested using various crack images with a label and the results showed over 90% of accuracy on crack classification and segmentation. Finally, the crack characteristics (length and thickness) of the crack image pictured from the field were analyzed, and the performance of the developed technique was verified by comparing the actual measured values and errors.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.171-178
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• 2021

In this paper, the author proposes a method for detecting modification of transmitted messages in C/C++ based Discrete Event System Specification (DEVS) simulation. When a message generated by a model instance is delivered to other model instances, it may be modified by some of the recipients. Such modifications may corrupt simulation results, which may lead to wrong decision making. In the proposed method, every model instance stores a copy of every transmitted message. Before the deletion of the transmitted message, the instance compares them. Once a modification has been detected, the method interrupt the current simulation run. The procedure is automatically performed by a simulator instance. Thus, the method does not require programmers to follow secure coding or to add specific codes in their models. The performance of the method is compared with a DEVS simulator.

• Journal of the Korean Geotechnical Society
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• v.38 no.11
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• pp.87-95
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• 2022

The geotechnical information constructed in the National Geotechnical Information DB System has been extensively used in design, construction, underground safety management, and disaster assessment. However, it is necessary to refine the geotechnical information because it has nearly 300,000 established cases containing a lot of missing or incorrect information. This research proposes a method for automatic quality control of geotechnical information using a fully connected neural network. Significantly, the anomalies in geotechnical information were detected using a database combining the standard penetration test results and strata information of Seoul. Consequently, the misclassification rate for the verification data is confirmed as 5.4%. Overall, the studied algorithm is expected to detect outliers of geotechnical information effectively.