• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.5
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• pp.803-813
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• 2013

As the developments of smart devices and social network services, the amount of data has been exploding. The world is facing Big data era. For these reasons, the Big data processing technology which is a new technology that can handle such data has attracted much attention. One of the most representative technologies is Hadoop. Hadoop Distributed File System(HDFS) designed to run on commercial Linux server is an open source framework and can store many terabytes of data. The initial version of Hadoop did not consider security because it only focused on efficient Big data processing. As the number of users rapidly increases, a lot of sensitive data including personal information were stored on HDFS. So Hadoop announced a new version that introduces Kerberos and token system in 2009. However, this system is vulnerable to the replay attack, impersonation attack and other attacks. In this paper, we analyze these vulnerabilities of HDFS security and propose a new protocol which complements these vulnerabilities and maintains the performance of Hadoop.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.126-136
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• 2020

Recently, unmanned aerial vehicles (UAV, Drone) are highly regarded for their potential in the agricultural field, and research and development are actively conducted for various purposes. Therefore, in this study, to present a framework for tracking research trends in UAV use in the agricultural field, we secured a keyword search strategy and analyzed social network, a methodology used to analyze recent research trends or technological trends as an analysis model applied. This study consists of three stages. As a first step in data acquisition, search terms and search formulas were developed for experts in accordance with the Keyword Search Strategy. Data collection was conducted based on completed search terms and search expressions. As a second step, frequency analysis was conducted by country, academic field, and journal based on the number of thesis presentations. Finally, social network analysis was performed. The analysis used the open source programming language 'Python'. Thanks to the efficiency and convenience of unmanned aerial vehicles, this field is growing rapidly and China and the United States are leading global research. Korea ranked 18th, and bold investment in this field is needed to advance agriculture. The results of this study's analysis could be used as important information in government policy making.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1431-1438
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• 2014

We analyzed the articles from "Kukje Shinmun" and "Busan Ilbo", which are two local newpapers of Busan Metropolitan City. The articles cover from January 1, 2013 to December 31, 2013. Meaningful pattern inherent in 2889 articles of which the title includes "Busan" and "Traffic" and related data was analyzed. Textmining method, which is a part of datamining, was used for the social network analysis (SNA). HDFS and MapReduce (from Hadoop ecosystem), which is open-source framework based on JAVA, were used with Linux environment (Uubntu-12.04LTS) for the construction of unstructured data and the storage, process and the analysis of big data. We implemented new algorithm that shows better visualization compared with the default one from R package, by providing the color and thickness based on the weight from each node and line connecting the nodes.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.4
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• pp.807-819
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• 2019

Greybox fuzzing is known as an effective method to discover unknown security flaws reside in software and has been actively researched today. However, most of greybox fuzzing tools require an executable file. Because of this, a library, which cannot be executed by itself requires an additional executable file for greybox fuzzing. Generating such an executable file is challengeable because it requires both understanding of the library and fuzzing. In this research, we suggest the approach to generate an executable file automatically for a library and implement this approach as a tool based on the LLVM framework. This tool shows that executable files and seed files can be generated automatically by static/dynamic analysis of a unit test in the target project. A generated executable file is compatible with various greybox fuzzers like AFL because it has a common interface for greybox fuzzers. We show the performance of this tool as code coverage and discovered unknown security bugs using generated executable files and seed files from open source projects through this tool.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.175-183
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• 2021

The study of the fine grained classification of images continues to develop, but the study of object recognition for animals with polymorphic properties is proceeding slowly. Using only pet images corresponding to dogs and cats, this paper aims to compare methods using image processing and methods using deep learning among methods of classifying species of animals, which are fine grained classifications. In this paper, Grab-cut algorithm is used for object segmentation by method using image processing, and method using Fisher Vector for image encoding is proposed. Other methods used deep learning, which has achieved good results in various fields through machine learning, and among them, Convolutional Neural Network (CNN), which showed outstanding performance in image recognition, and Tensorflow, an open-source-based deep learning framework provided by Google. For each method proposed, 37 kinds of pet images, a total of 7,390 pages, were tested to verify and compare their effects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.396-402
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• 2022

User interactions are being developed in various forms, and in particular, interactions using human gestures are being actively studied. Among them, hand gesture recognition is used as a human interface in the field of realistic media based on the 3D Hand Model. The use of interfaces based on hand gesture recognition helps users access media media more easily and conveniently. User interaction using hand gesture recognition should be able to view images by applying fast and accurate hand gesture recognition technology without restrictions on the computer environment. This paper developed a fast and accurate user hand gesture recognition algorithm using the open source media pipe framework and machine learning's k-NN (K-Nearest Neighbor). In addition, in order to minimize the restriction of the computer environment, a stereoscopic image control system based on user hand gesture recognition was designed and implemented using a web service environment capable of Internet service and a docker container, a virtual environment.

• Smart Structures and Systems
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• v.30 no.3
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• pp.221-237
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• 2022

This paper is concerned with nonlinear modeling and efficient numerical simulation of electrostrictive materials and structures. Two types of such materials are considered: relaxor ferroelectric ceramics and electrostrictive polymers. For ceramics, a geometrically linear formulation is developed, whereas polymers are studied in a geometrically nonlinear regime. In the paper, we focus on constitutive modeling first. For the reversible constitutive response under consideration, we introduce the augmented Helmholtz free energy, which is composed of a purely elastic part, a dielectric part and an augmentation term. For the elastic part, we involve an additive decomposition of the strain tensor into an elastic strain and an electrostrictive eigenstrain, which depends on the polarization of the material. In the geometrically nonlinear case, a corresponding multiplicative decomposition of the deformation gradient tensor replaces the additive strain decomposition used in the geometrically linear formulation. For the dielectric part, we first introduce the internal energy, to which a Legendre transformation is applied to compute the free energy. The augmentation term accounts for the contribution from vacuum to the energy. In our formulation, the augmented free energy depends not only on the strain and the electric field, but also on the polarization and an internal polarization; the latter two are internal variables. With the constitutive framework established, a Finite Element implementation is briefly discussed. We use high-order elements for the discretization of the independent variables, which include also the internal variables and, in case the material is assumed incompressible, the hydrostatic pressure, which is introduced as a Lagrange multiplier. The elements are implemented in the open source code Netgen/NGSolve. Finally, example problems are solved for both, relaxor ferroelectric ceramics and electrostrictive polymers. We focus on thin plate-type structures to show the efficiency of the numerical scheme and its applicability to thin electrostrictive structures.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.6
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• pp.1091-1102
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• 2022

Robotic systems have developed very rapidly over the past decade. Robot Operating System is an open source-based software framework for the efficient development of robot operating systems and applications, and is widely used in various research and industrial fields. ROS applications may contain various vulnerabilities. Various studies have been conducted to monitor the excution of these ROS applications at runtime. In this study, we propose a real-time attack detection system using event-based runtime monitoring in ROS 2. Our attack detection system extends tracetools of ros2_tracing to instrument events into core libraries of ROS 2 middleware layer and monitors the events during runtime to detect attacks on the application layer through out-of-order execution of the APIs.

• Smart Media Journal
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• v.11 no.2
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• pp.70-76
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• 2022

IoT application development using a cloud server causes problems such as data transmission and reception delay, network traffic, and cost for real-time processing support in network connected hardware. To solve this problem, edge cloud-based platforms can use neuromorphic hardware to enable fast data transfer. In this paper, we propose a model optimization method for supporting spiking neural networks on FPGA hardware. We focused on auto-adjusting network model parameters optimized for neuromorphic hardware. The proposed method performs optimization to show higher performance based on user requirements for accuracy. As a result of performance analysis, it satisfies all requirements of accuracy and showed higher performance in terms of expected execution time, unlike the naive method supported by the existing open source framework.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.273-283
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• 2022

Banking and finance is a broad term that incorporates a variety of smaller, more specialized subjects such as corporate finance, tax finance, and insurance finance. A virtual assistant that assists users in searching for information about banking and finance terms might be an extremely beneficial tool for users. In this study, we explored the process of searching for information, seeking opportunities, and developing a virtual assistant in the first stages of starting learning and understanding Vietnamese to increase effectiveness and save time, which is also an innovative business practice in Use-case Vietnam. We built the FIBA2020 dataset and proposed a pipeline that used Natural Language Processing (NLP) inclusive of Natural Language Understanding (NLU) algorithms to build chatbot applications. The open-source framework RASA is used to implement the system in our study. We aim to improve our model performance by replacing parts of RASA's default tokenizers with Vietnamese tokenizers and experimenting with various language models. The best accuracy we achieved is 86.48% and 70.04% in the ideal condition and worst condition, respectively. Finally, we put our findings into practice by creating an Android virtual assistant application using the model trained using Whitespace tokenizer and the pre-trained language m-BERT.