• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1433-1436
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• 2012

프로젝트의 성공 가능성을 높일 수 있는 요인들에 대한 연구결과는 지속되고 있지만, 측정지표에 대한 선행연구는 건설분야를 제외하고는 SW 분야에서는 아직 초보적인 단계이다. 특히, 범위(Scope)는 프로젝트 관리에 있어 중요한 부분으로 지표의 발굴이 필요한 상황이다. 따라서 본 연구에서는 효율적인 WBS의 작성을 위해서는 명확한 Project Scope Statement가 제시되어야 한다는 전제하에, Project Scope Statement와 WSB 간에 서로 영향을 미치는 요인들을 연구하고자 한다. 또한 명확한 범위정의라는 성공목표를 위한 세부적인 지표 도출을 하고자 한다. 본 연구의 목적은 SW 프로젝트 측면에 있어 범위관리 관련 주요요인을 분석하여 범위관련 제반 문제점을 사전에 탐지하기 위한 PI, KPI를 정의 발견하는데 있다.

• Review of KIISC
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• v.31 no.3
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• pp.61-71
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• 2021

최근 블록체인 기술의 적용 범위가 전 산업으로 확대되고 있으며, 고부가가치 정보와 디지털 자산이 블록체인 분산 데이터베이스에 저장되고 관리되면서 블록체인을 대상으로 하는 보안 위협이 급격히 증가하고 있다. 특히 가용성 저하 공격, 분산 서비스 거부 공격, 비정상 거래, 악의적 거래, 51% 공격과 같이 블록체인을 대상으로 한 공격 기법이 고도화되고 피해 규모가 커지고 있다. 블록체인은 금융, 물류, 의료, 인증 등 전 산업 분야에 활용될 가능성이 높아지고 있어서 블록체인 네트워크 보안 위협을 신속하고 정확하게 탐지하는 기술에 대한 연구가 요구된다. 본 논문에서는 블록체인 네트워크 보안 위협에 대해 분석하고, 주요 위협 탐지 기술과 최신 동향을 분석한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.99-101
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• 2022

이상 행동을 탐지하는 딥러닝 기반 검지 시스템은 동영상 기반 데이터로부터 움직임을 보이는 객체를 추적하고 그 객체의 행동을 분석하여 정상적인 행동 범위를 벗어나는 패턴을 보이는 영역을 이상으로 탐지한다. 특히 생성적 적대 신경망(GAN)과 광학 흐름 추정(Optical flow estimation) 기법을 활용하여 움직임에 대한 특징 정보를 추출하고 이를 학습하여 행동 패턴에 대한 모델링을 수행한다. 모델 학습 및 테스트에 활용되는 데이터셋의 해상도가 낮거나 이상 행동을 표현하는 특징 정보가 부족할 경우 최종 모델 성능에 부정적 영향을 미치게 되며, 특히 광학 흐름이 표현하는 이동량 측면에서 차이가 크게 나지 않는 이상 객체의 경우 탐지가 정확하게 이뤄지지 않는다. 본 연구에서는 동영상 프레임에서 나타나는 객체의 평균 종횡비를 구하고 정상적인 비율을 벗어나는 객체에 대해서 이상 행동을 취하는 샘플로 처리하는 후처리단 모듈을 제안하여 최종적인 모델 성능을 향상시키는 방법을 고안한다.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.365-377
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• 2020

Continuous monitoring and immediate response is essential to protect the national maritime territory and maritime resources from the activities of illegal ships. Synthetic Aperture Radar (SAR) images with a wide range of images are effective for maritime surveillance asthe weather and day-night conditions rarely affect to image acquisition. However, an effective ship detection is not easy due to the huge data size of SAR images and various characteristics such as the speckle noise. In this study, the Human Visual Attention System (HVAS) algorithm was applied to KOMPSAT-5 to extract the initial targets, and the SAR-Split algorithm depending on the imaging modes was used to remove false alarms. The detected targets were finally selected by the Constant False Alarm Rate (CFAR) algorithm and matched with the ship's Automatic Identification System (AIS) information. Overall, the detected targets were well matched with AIS data, but some false alarms by ship wakes were observed. The detection rate was about 80% in ES mode and about 64% in ST mode. It is expected that the developed ship detection algorithm will contribute to the construction of a wide area maritime surveillance network.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.537-546
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• 2017

This study aims to develop the floating debris detection algorithm using a Unmanned Aerial Vehicle (UAV) and multispectral sensors. In addition, the occurrence range of floating debris was estimated by applying the algorithm. An aerial photograph using an unmanned aerial vehicle was used to generate an orthoimage that can calculate the area. A spectrum survey of water, plants litter, polystyrene foam etc. was conducted. After obtaining spectroscopic characteristics of floating debris and water, the River Floating Debris (RFD) index was calculated. And we detected the floating debris through band combination of sensor using RFD. As a result of the RFD application, accumulation zone of floating debris was confirmed at three sites in the orthoimage. It was estimated that a lot of floating debris was accumulated at 0.82 ha ($8,200m^2$), which is corresponding to 3.6% including the accumulation zone.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.5
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• pp.509-517
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• 2011

Recently, large scale of the damage from the natural disasters are occurring frequently such as Japanese and New Zealand's earthquake. Collecting information quickly and accurately from damaged area is important for effective react in emergency situations. UAV is effective method to collect information because it can fly low attitude and spend small operational costs/time. In this study, collecting data about the UAV regulations are analyzed for effective UAV operation in disaster detection. And Improvement of Regulations were proposed about Problem of UAV Operation. Regulation of UAV for disaster detecting is not exist. But It's possible to classify into Ultra Light Plane. So addition of some clauses like definition, scope and air-borne equipment for UAV will be needed. Also, it is difficult to manage effectively because of process about flight permission, therefore it is need to enact exceptional regulations to solve this problem. More analytical research based on applications of UAV operation for disaster detection will be present improvement of disaster detection and damage investigation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.223-228
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• 2017

In this paper, we are proposing an optimal design of wideband pulsed type gamma-ray sensors. These sensors were manufactured based on the design results and after word electrical properties were analyzed. The sensor input parameters were derived on the basis of pulsed gamma-ray spectrum and time-dependent energy rate, and the output current which were derived on the basis of the sensor sensitivity control circuit. Pulsed gamma-ray sensors were designed using the TCAD simulators. The design results show that the optimal Epi layer thickness is 45um with the applied voltage 3.3V and the diameter is 2.0mm. The doping concentrations are as follows : N-type is an Arsenic as $1{\times}10^{19}/cm^3$, P-type is a Boron as $1{\times}10^{19}/cm^3$ and Epi layer is Phosphorus as $3.4{\times}10^{12}/cm^3$. The fabricated sensor was a leakage current, 12pA at voltage -3.3V and fully depleted mode at voltage -5V. A test result of pulsed radiation shows that the sensor gives out the optimal photocurrent.

• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.157-165
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• 2004

The paper suggests that web-server security management system will be able to detect the web service attack accurately and swiftly which is keeping on increasing at the moment and reduce the possibility of the false positive detection. This system gathers the results of many unit security modules at the real time and enhances the correctness of the detection through the correlation analysis procedure. The unit security module consists of Network based Intrusion Detection System module. File Integrity Check module. System Log Analysis module, and Web Log Analysis and there is the Correlation Analysis module that analyzes the correlations on the spot as a result of each unit security module processing. The suggested system provides the feasible framework of the range extension of correlation analysis and the addition of unit security module, as well as the correctness of the attack detection. In addition, the attack detection system module among the suggested systems has the faster detection time by means of restructuring Snort with multi thread base system. WSM will be improved through shortening the processing time of many unit security modules with heavy traffic.

• Convergence Security Journal
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• v.18 no.5_1
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• pp.45-51
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• 2018

As data utilization and importance becomes important, data-related accidents and damages are gradually increasing. Especially, insider threats are the most harmful threats. And these insider threats are difficult to detect by traditional security systems, so rule-based abnormal behavior detection method has been widely used. However, it has a lack of adapting flexibly to changes in new attacks and new environments. Therefore, in this paper, we propose an adaptive anomaly movement detection framework based on a statistical Markov model to detect insider threats in advance. This is designed to minimize false positive rate and false negative rate by adopting environment factors that directly influence the behavior, and learning data based on statistical Markov model. In the experimentation, the framework shows good performance with a high F2-score of 0.92 and suspicious behavior detection, which seen as a normal behavior usually. It is also extendable to detect various types of suspicious activities by applying multiple modeling algorithms based on statistical learning and environment factors.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.251-255
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• 2008

We have developed an electronic aids, called SmartWand, which can help visually impaired people walk safely and tell them an object's color and environmental brightness SmartWand can inform visually impaired people of the dangerous obstacles around which they can't notice by the white cane such as a large panel with supporting poles on the street. Especially we have lmproved the previous version of SmartWand by reflecting the result of user study.