• Title/Summary/Keyword: 탐지방안

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Pentesting-Based Proactive Cloud Infringement Incident Response Framework (모의해킹 기반 사전 예방적 클라우드 침해 사고 대응 프레임워크)

  • Hyeon No;Ji-won Ock;Seong-min Kim
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.3
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    • pp.487-498
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    • 2023
  • Security incidents using vulnerabilities in cloud services occur, but it is difficult to collect and analyze traces of incidents in cloud environments with complex and diverse service models. As a result, the importance of cloud forensics research has emerged, and infringement response scenarios must be designed from the perspective of cloud service users (CSUs) and cloud service providers (CSPs) based on representative security threat cases in the public cloud service model. This simulated hacking-based proactive cloud infringement response framework can be used to respond to the cloud service critical resource attack process from the viewpoint of vulnerability detection before cyberattacks occur on the cloud, and can also be expected for data acquisition. Therefore, in this paper, we propose a framework for preventive cloud infringement based on simulated hacking by analyzing and utilizing Cloudfox, a cloud penetration test tool.

A Study on the Calculation of the Number of Rescuers at Fire Sites Using Wireless Signals of Mobile Phones (화재 현장에서 휴대전화 무선 신호를 활용한 구조대원 투입 인원수 산출 연구)

  • Kim, Younghyun;Kim, Boseob;Lee, Sungwoo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.275-276
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    • 2021
  • In the event of a fire in a complex, the identification of isolated people's location information is delayed, resulting in many casualties. In order to prevent such an accident, research on estimating the location of the requesters by detecting the wireless signal of the mobile phone at fire sites is in progress. The main concept is to use a wireless signal scanner to detect the wireless signal of a mobile phones at fire sites, and then position the mobile phone based on this. However, it is difficult to secure visibility at the fire site due to the smoke, and there is a difficulty in rescuing requesters in need compared with general disaster sites. Therefore, it will be one of the important issues to be solved to determine the minimum number of rescuers to be deployed according to the number and condition of the requesters. In this study, we propose a method to calculate the number of rescuers put to fire sites by using the radio signal generated from mobile phones and the information generated from the inertial sensor of the mobile phones.

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Design of Face with Mask Detection System in Thermal Images Using Deep Learning (딥러닝을 이용한 열영상 기반 마스크 검출 시스템 설계)

  • Yong Joong Kim;Byung Sang Choi;Ki Seop Lee;Kyung Kwon Jung
    • Convergence Security Journal
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    • v.22 no.2
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    • pp.21-26
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    • 2022
  • Wearing face masks is an effective measure to prevent COVID-19 infection. Infrared thermal image based temperature measurement and identity recognition system has been widely used in many large enterprises and universities in China, so it is totally necessary to research the face mask detection of thermal infrared imaging. Recently introduced MTCNN (Multi-task Cascaded Convolutional Networks)presents a conceptually simple, flexible, general framework for instance segmentation of objects. In this paper, we propose an algorithm for efficiently searching objects of images, while creating a segmentation of heat generation part for an instance which is a heating element in a heat sensed image acquired from a thermal infrared camera. This method called a mask MTCNN is an algorithm that extends MTCNN by adding a branch for predicting an object mask in parallel with an existing branch for recognition of a bounding box. It is easy to generalize the R-CNN to other tasks. In this paper, we proposed an infrared image detection algorithm based on R-CNN and detect heating elements which can not be distinguished by RGB images.

asset management framework for low-carbon water distribution system (저탄소 상수도 관망을 위한 자산관리 체계 구축)

  • Kim, Beomjin;Lee, Jaeyeon;Lee, Seungyub
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.183-183
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    • 2022
  • 최근 몇 년 동안 기후변화에 대응하기 위한 탄소중립 혹은 저탄소 운영의 중요성이 강조되어왔다. 상수도 관망은 직접적인 탄소 배출 시설물은 아니지만, 상수도 관망의 운영 그리고 구성요소의 제조부터 폐기까지의 전 생애주기 동안 막대한 양의 에너지를 사용하는데, 이러한 에너지의사용이 탄소 배출에 간접적인 영향을 주는 것으로 알려져 있다. 특히 수자원공사에 따르면, '17년 기준 수도사업 관련 전기 사용에 따른 간접 배출이 70만tCO2eq에 이르는 것으로 보고되고 있어, 에너지의 효율적인 운영 및 자산관리 체계의 필요성이 커지고 있는 실정이다. 상수도 관망의 에너지 효율에 영향을 주는 요인은 크게 구성요소의 노후와 누수로 구분할 수 있다. 본 연구에서는 상수도 관망 관로 별 노후와 누수 여부를 판단하여 교체 전략을 수립할 수 있는 자산관리 모형을 제안하고 관로별 에너지 효율을 시각화하여 전반적인 자산관리에 근거를 제시하고자 한다. 모형은 최적화 기법을 통한 관로별 기능적 노후도 산정 및 누수 탐지, 관만 내 누수 지역화, 에너지 효율 시각화 등 총 3개의 모듈로 구성되어 있다. 제안한 모형은 고도의 차이가 큰 국내 D시 가상 관망에 적용하였다. 해당 관망에 다양한 관로의 노후 및 누수 상황을 가정하여 가상의 데이터를 생성하고 이를 토대로 관로별 기능적 노후와 누수 조건을 고려하여 해당 모형을 검증한다. 또한, 노후와 누수에 따른 가상 상황별 관로의 자산관리 의사결정 예시를 제공하여 향후 모형의 활용에 대한 가이드 라인을 제시한다. 마지막으로 관망 내 설치된 감압밸브를 터빈으로 전환하여 관망 운영 단계에서 무의미하게 소산되는 열에너지를 회수하는 방안을 검증하였다. 최적화 기법을 통해 비용 대비 최적 터빈 설치 지역을 선정하였고 향후 터빈 설치에 고려해야 할 사항을 정리한다. 본 연구에서의 결과는 향후 종합적인 저탄소형 상수도 관망을 위한 초석을 제공할 것으로 기대한다.

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Study on Energy Efficiency Improvement in Manufacturing Core Processes through Energy Process Innovation (에너지 프로세스 혁신을 통한 제조 핵심 공정의 에너지 효율화 방안 연구)

  • Sang-Joon Cho;Hyun-Mu Lee;Jin-Soo Lee
    • Journal of Advanced Technology Convergence
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    • v.2 no.4
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    • pp.43-48
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    • 2023
  • Globally, there is a collaborative effort to achieve global carbon neutrality in response to climate change. In the case of South Korea, greenhouse gas emissions are rapidly increasing, presenting an urgent situation that requires resolution. In this context, this study developed a thermal energy collection device named a 'steam trap' and created an AI model capable of predicting future electricity usage by collecting energy usage data through steam traps. The average accuracy of electricity usage prediction with this AI model was 96.7%, demonstrating high precision. Consequently, the AI model enables the prediction and management of days with high electricity consumption and identifies which facilities contribute to elevated power usage. Future research aims to optimize energy consumption efficiency through efficient equipment operation using anomaly detection in steam traps and standardizing energy management systems, with the ultimate goal of reducing greenhouse gas emissions.

Derivation of Green Coverage Ratio Based on Deep Learning Using MAV and UAV Aerial Images (유·무인 항공영상을 이용한 심층학습 기반 녹피율 산정)

  • Han, Seungyeon;Lee, Impyeong
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1757-1766
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    • 2021
  • The green coverage ratio is the ratio of the land area to green coverage area, and it is used as a practical urban greening index. The green coverage ratio is calculated based on the land cover map, but low spatial resolution and inconsistent production cycle of land cover map make it difficult to calculate the correct green coverage area and analyze the precise green coverage. Therefore, this study proposes a new method to calculate green coverage area using aerial images and deep neural networks. Green coverage ratio can be quickly calculated using manned aerial images acquired by local governments, but precise analysis is difficult because components of image such as acquisition date, resolution, and sensors cannot be selected and modified. This limitation can be supplemented by using an unmanned aerial vehicle that can mount various sensors and acquire high-resolution images due to low-altitude flight. In this study, we proposed a method to calculate green coverage ratio from manned or unmanned aerial images, and experimentally verified the proposed method. Aerial images enable precise analysis by high resolution and relatively constant cycles, and deep learning can automatically detect green coverage area in aerial images. Local governments acquire manned aerial images for various purposes every year and we can utilize them to calculate green coverage ratio quickly. However, acquired manned aerial images may be difficult to accurately analyze because details such as acquisition date, resolution, and sensors cannot be selected. These limitations can be supplemented by using unmanned aerial vehicles that can mount various sensors and acquire high-resolution images due to low-altitude flight. Accordingly, the green coverage ratio was calculated from the two aerial images, and as a result, it could be calculated with high accuracy from all green types. However, the green coverage ratio calculated from manned aerial images had limitations in complex environments. The unmanned aerial images used to compensate for this were able to calculate a high accuracy of green coverage ratio even in complex environments, and more precise green area detection was possible through additional band images. In the future, it is expected that the rust rate can be calculated effectively by using the newly acquired unmanned aerial imagery supplementary to the existing manned aerial imagery.

Convergence of Remote Sensing and Digital Geospatial Information for Monitoring Unmeasured Reservoirs (미계측 저수지 수체 모니터링을 위한 원격탐사 및 디지털 공간정보 융합)

  • Hee-Jin Lee;Chanyang Sur;Jeongho Cho;Won-Ho Nam
    • Korean Journal of Remote Sensing
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    • v.39 no.5_4
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    • pp.1135-1144
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    • 2023
  • Many agricultural reservoirs in South Korea, constructed before 1970, have become aging facilities. The majority of small-scale reservoirs lack measurement systems to ascertain basic specifications and water levels, classifying them as unmeasured reservoirs. Furthermore, continuous sedimentation within the reservoirs and industrial development-induced water quality deterioration lead to reduced water supply capacity and changes in reservoir morphology. This study utilized Light Detection And Ranging (LiDAR) sensors, which provide elevation information and allow for the characterization of surface features, to construct high-resolution Digital Surface Model (DSM) and Digital Elevation Model (DEM) data of reservoir facilities. Additionally, bathymetric measurements based on multibeam echosounders were conducted to propose an updated approach for determining reservoir capacity. Drone-based LiDAR was employed to generate DSM and DEM data with a spatial resolution of 50 cm, enabling the display of elevations of hydraulic structures, such as embankments, spillways, and intake channels. Furthermore, using drone-based hyperspectral imagery, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were calculated to detect water bodies and verify differences from existing reservoir boundaries. The constructed high-resolution DEM data were integrated with bathymetric measurements to create underwater contour maps, which were used to generate a Triangulated Irregular Network (TIN). The TIN was utilized to calculate the inundation area and volume of the reservoir, yielding results highly consistent with basic specifications. Considering areas that were not surveyed due to underwater vegetation, it is anticipated that this data will be valuable for future updates of reservoir capacity information.

A Study on Optimal Operation for Flare systems (플레어 시스템의 최적 운영방안에 대한 연구)

  • Song, Bang-Un;Bok, Hyeong-Jun;Woo, In-Sung
    • Journal of the Korean Institute of Gas
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    • v.23 no.6
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    • pp.1-7
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    • 2019
  • Most oil refineries and chemical plants have flare systems designed to mitigate pressure rises in process facilities in case of emergencies that require the release of large amounts of gas due to sudden process shutdowns such as power outages. However, the rise of the flame of the flare system causes civil complaints from residents around the factory due to visible pollution, and economic loss occurs in the company, which requires constant management. In this study, two items were diagnosed and analyzed in order to derive the optimal operation method of flare system. First, to detect the cause of the rise in flame height, the acoustic leak detector was used to check gas leaks in safety valves and pressure control valves. Second, to identify the cause of flame instability, the pulsation phenomenon was diagnosed through the CFD simulation and modeling experiments of the sealing drum. By confirming the leak at 4.3% of the safety valve and 10% of the pressure control valve, the cause of abnormal sparking was derived. The information presented in this study can be easily applied to any company that has a flare system, and is expected to prevent complaints and product loss.

Status of Development of Pyroprocessing Safeguards at KAERI (한국원자력연구원 파이로 안전조치 기술개발 현황)

  • Park, Se-Hwan;Ahn, Seong-Kyu;Chang, Hong Lae;Han, Bo Young;Kim, Bong Young;Kim, Dongseon;Kim, Ho-Dong;Lee, Chaehun;Oh, Jong-Myeong;Seo, Hee;Shin, Hee-Sung;Won, Byung-Hee;Ku, Jeong-Hoe
    • Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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    • v.15 no.3
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    • pp.191-197
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    • 2017
  • The Korea Atomic Energy Research Institute (KAERI) has developed a safeguards technology for pyroprocessing based on the Safeguards-By-Design (SBD) concept. KAERI took part in a Member-State Support Program (MSSP) to establish a pyroprocessing safeguards approach. A Reference Engineering-scale Pyroprocessing Facility (REPF) concept was designed on which KAERI developed its safeguards system. Recently the REPF is being upgraded to the REPF+, a scaled-up facility. For assessment of the nuclear-material accountancy (NMA) system, KAERI has developed a simulation program named Pyroprocessing Material Flow and MUF Uncertainty Simulation (PYMUS). The PYMUS is currently being upgraded to include a Near-Real-Time Accountancy (NRTA) statistical analysis function. The Advanced Spent Fuel Conditioning Process Safeguards Neutron Counter (ASNC) has been updated as Non-Destructive Assay (NDA) equipment for input-material accountancy, and a Hybrid Induced-fission-based Pu-Accounting Instrument (HIPAI) has been developed for the NMA of uranium/transuranic (U/TRU) ingots. Currently, performance testing of Compton-suppressed Gamma-ray measurement, Laser-Induced Breakdown Spectroscopy (LIBS), and homogenization sampling are underway. These efforts will provide an essential basis for the realization of an advanced nuclear-fuel cycle in the ROK.

GIS based Effective Methodology for GAS Accident Management (GIS를 이용한 효율적인 가스사고관리 방법에 관한 연구)

  • 김태일;김계현;전방진;곽태식
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2004.03a
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    • pp.399-406
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    • 2004
  • 최근 급속한 도시의 팽창과 산업의 발전으로 인하여 가스시설은 급속히 확대되고 있는 실정이다. 이러한 가스시설물의 중요성을 인식하고 많은 도시가스업체에서는 가스관망 시설정보를 전산화하여 항상 최신의 현황을 유지할 수 있는 가스시설물관리시스템을 개발하여 사용하고 있다. 그러나 이러한 시스템은 가스시설물의 현황파악 및 유지관리를 위한 기본적인 기능만을 제공하는 관계로, 가스 누출사고 발생시 정확한 사태의 파악과 함께 신속한 대책 마련을 위한 의사결정 지원이 어려운 실정이다. 따라서 체계적인 가스사고관리를 수행할 수 있는 응용시스템의 필요성이 증대되고 있다. 이러한 시점에서 본 연구에서는 가스사고분석을 신속하고 체계적으로 수행할 수 있는 가스사고관리 적용알고리즘 분석 및 최적의 알고리즘을 정립하여 가스사고관리시스템을 구현하였다. 본 연구를 통한 결과는 1ㆍ2차 차단밸브의 산정이 가능해짐으로써 빈번한 가스 누출사고 발생시 실시간으로 적정대처방안의 제시가 가능하게 되었다. 또한, 누출 최대가스량을 제시함으로써 누출에 대한 피해예상 분석을 위한 정보 제공 및 가스의 신속한 재공급을 위해 필요한 의사결정 지원 정보의 제공이 가능하게 되었다. 아울러, 가스누출사고에 의한 가스공급중단 관로 및 수용가에 대한 속성현황의 파악은 물론 시각적인 도식을 통한 전체적 현황파악이 가능하였다. 이러한 가스사고관리시스템의 개발을 통하여 사고 발생시 신속한 사고방안 제시 및 사고피해의 최소화를 위해 필요한 의사결정 지원 정보의 제공이 가능하게 됨으로써 국민의 안전 및 복지와 도시가스업체의 업무 효율화로 인한 예산절감 효과를 기대할 수 있다. 가시권 분석기능을 이용하여 실제 지형공간상에서 전파경로 손실치를 도시화함으로써 전파관리자가 무선서비스지역 설계, 전파음영지역 판단, 최적 중계기와 기지국 위치 선정에 기여할 것으로 판단된다.하지 않은 지역과 서로 다른 분광특성을 나타내므로 별도의 Segment를 형성하게 된다. 따라서 임상도의 경계선으로부터 획득된 Super-Object의 분광반사 값과 그 안에서 형성된 Sub-Object의 분광반사값의 차이를 이용하여 임상도의 갱신을 위한 변화지역을 탐지하였다.라서 획득한 시추코아에 대해서도 각 연구기관이 전 구간에 대해 동일하게 25%의 소유권을 가지고 있다. ?스굴 시추사업은 2008년까지 수행될 계획이며, 시추작업은 2005년까지 완료될 계획이다. 연구 진행과 관련하여, 공동연구의 명분을 높이고 분석의 효율성을 높이기 위해서 시료채취 및 기초자료 획득은 4개국의 연구원이 모여 공동으로 수행한 후의 결과물을 서로 공유하고, 자세한 전문분야 연구는 각 국의 대표기관이 독립적으로 수행하는 방식을 택하였다 ?스굴에 대한 제1차 시추작업은 2004년 3월 말에 실시하였다. 시추작업 결과, 약 80m의 시추 코아가 성공적으로 회수되어 현재 러시아 이르쿠츠크 지구화학연구소에 보관중이다. 이 시추코아는 2004년 8월 중순경에 4개국 연구팀원들에 의해 공동으로 기재된 후에 분할될 계획이다. 분할된 시료는 국내로 운반되어 다양한 전문분야별 연구에 이용될 것이다. 한편, 제2차 시추작업은 2004년 12월에서 2005년 2월 사이에 실시될 계획이다. 수백만년에 이르는 장기간에 걸쳐 지구환경변화 기록이 보존되어 있는 ?스굴호에 대한

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