• Title/Summary/Keyword: Security Architecture

Search Result 1,092, Processing Time 0.027 seconds

Study on Education Content Delivery System in Hybrid P2P based Computing Environment (혼합형 P2P 기반 컴퓨팅환경에서의 교육 컨텐츠 전송 시스템에 대한 연구)

  • Kim, Jin-Il
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • v.9 no.2
    • /
    • pp.658-661
    • /
    • 2005
  • Internet-based client/server architecture of Contents Delivery System suffers from frequent disconnections and security treats caused by dependency of the server or overload. But, We reached the limit to the increase of the server because a contents quality enhance and Internet user explosively increase. Therefore, a P2P based computing methods are used for sloving these issues. In this paper, We implement and design the Education Content Delivery System for cyber education system using idle Computing Power in P2P computing to share computing resources. We implement not only Internet infrastructure but also satellite infrastructure system, and designed to transfer real-time or non real-time contents.

  • PDF

The Status and Features of the DMZ Forested Wetlands Fauna - Focusing on the Kyongui Line in Paju - (DMZ 산림습지의 식생 현황과 특성에 관한 연구 - 파주 경의선 지역을 중심으로 -)

  • Park, Mi-Young;Cho, Dong-Gil;Kim, Kwi-Gon
    • Journal of the Korean Society of Environmental Restoration Technology
    • /
    • v.8 no.5
    • /
    • pp.28-38
    • /
    • 2005
  • The De-militarized Zone(DMZ) on the Korean Peninsula is ecologically conserved and naturally developed as access to the area has been controlled in the past five decades. As a result, biodiversity and wetlands are developed very well, but they have not been sufficiently surveyed due to land mines and security reasons. Focusing on the Kyongui Line area in Paju DMZ, this study aims at examining the status of forested wetlands in detail through an on-site survey and understanding the features of forested wetlands in DMZ. The forested wetlands of Paju Kyongui Line area are inhabited by naturally grown Salix koreensis Andress. and Acer ginnale Maxim. and affected by Sacheon Basin region extensively. As the topography of this region is created of inundated area and gentle ground, it is easily affected by hydrology and irrigation and has ideal conditions as forested wetlands. In addition, forest wetlands in this area were used as agricultural land in the past but now transformed into palustrine forested wetlands after being deserted for long time. However, as construction of roads and railways increasingly blocks water paths, the coverage of Robinia pseudoacacia L. and Amorpha fruticosa L. is on the rise, which indicates that forestedwetlands are gradually becoming inland over time.

3X Serial GF(2m) Multiplier on Polynomial Basis Finite Field (Polynomial basis 방식의 3배속 직렬 유한체 곱셈기)

  • 문상국
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2004.05b
    • /
    • pp.255-258
    • /
    • 2004
  • Efficient finite field operation in the elliptic curve (EC) public key cryptography algorithm, which attracts much of latest issues in the applications in information security, is very important. Traditional serial finite multipliers root from Mastrovito's serial multiplication architecture. In this paper, we adopt the polynomial basis and propose a new finite field multiplier, inducing numerical expressions which can be applied to exhibit 3 times as much performance as the Mastrovito's. We described the proposed multiplier with HDL to verify and evaluate as a proper hardware IP. HDL-implemented serial GF (Galois field) multiplier showed 3 times as fast speed as the traditional serial multiplier's adding only Partial-sum block in the hardware.

  • PDF

Dynamic Analysis of Floating Bodies Considering Multi-body Interaction Effect (다물체 연성효과를 고려한 부유체의 동적거동 안전성 해석)

  • Kim, Young-Bok;Kim, Moo-Hyun;Kim, Yong-Yook
    • Journal of the Society of Naval Architects of Korea
    • /
    • v.46 no.6
    • /
    • pp.659-666
    • /
    • 2009
  • Recently, there are several problems in space, contiguity and facility of the existing harbors issued due to the trend of enlarging the container capacity of the large container vessel, the Mobile Harbor has been proposed conceptually as an effective solution for those problems. This concept is a kind of transfer loader of the containers from the large container ship, which is a floating barge with a catamaran type in the underwater part, and so prompt maneuverability and work effectiveness. For the safe mooring of two floating bodies, a container and the mobile harbor, in the near sea apart from the quay, a robot arm mooring facility specially devised would be designed and verified through comparison study under various environmental sea condition in the inner and outer harbor. DP system (Dynamic Positioning System) using the azimuth thruster and a pneumatic fender, etc, will be considered as a next research topic for the mooring security of multi-body floaters.

A comparative study of machine learning methods for automated identification of radioisotopes using NaI gamma-ray spectra

  • Galib, S.M.;Bhowmik, P.K.;Avachat, A.V.;Lee, H.K.
    • Nuclear Engineering and Technology
    • /
    • v.53 no.12
    • /
    • pp.4072-4079
    • /
    • 2021
  • This article presents a study on the state-of-the-art methods for automated radioactive material detection and identification, using gamma-ray spectra and modern machine learning methods. The recent developments inspired this in deep learning algorithms, and the proposed method provided better performance than the current state-of-the-art models. Machine learning models such as: fully connected, recurrent, convolutional, and gradient boosted decision trees, are applied under a wide variety of testing conditions, and their advantage and disadvantage are discussed. Furthermore, a hybrid model is developed by combining the fully-connected and convolutional neural network, which shows the best performance among the different machine learning models. These improvements are represented by the model's test performance metric (i.e., F1 score) of 93.33% with an improvement of 2%-12% than the state-of-the-art model at various conditions. The experimental results show that fusion of classical neural networks and modern deep learning architecture is a suitable choice for interpreting gamma spectra data where real-time and remote detection is necessary.

A Study on Identification of the Heat Vulnerability Area - Case Study in Chungcheongnamdo - (폭염 취약지역 도출에 관한 연구 - 충청남도를 대상으로 -)

  • Lee, Gyeongjin;Cha, Jungwoo
    • Journal of Korean Society of Rural Planning
    • /
    • v.25 no.1
    • /
    • pp.67-74
    • /
    • 2019
  • This study is to identify the heat vulnerability area as represented by heat risk factors which could be attributable to heat-related deaths. The heat risk factors were temperature, Older Adults(OA), Economic Disadvantage(ED), Accessibility of Medical Services(AMS), The population Single Person Households(SPH). The factors are follow as; the temperature means to the number of days for decades average daily maximum temperature above $31^{\circ}C$, the Older Adults means to population ages 65 and above, furthermore, the Economic Disadvantage means to the population of Basic Livelihood Security Recipients(BLSR), the Accessibility of Medical Services(AMS) means to 5 minutes away from emergency medical services. The results of the analysis are showed that the top-level of temperature vulnerability areas is Dong, the top-level of vulnerability OA areas is Eup, the top-level of AMS vulnerability is Eup. Moreover, the top-level of vulnerability ED area appears in the Eup and Dong. The result of analysing relative importance to each element, most of the Eup were vulnerable to heat. Since, there are many vulnerable groups such as Economic Disadvantage, Older Adults in the Eup. We can be figured out estimated the number of heat-related deaths was high in the Eup and Dong by the data of emergency activation in the Chungcheongnam-do Fire Department. Therefore, the result of this study could be reasonable.

The Design of Remote Monitoring and Warning System for Dangerous Chemicals Based on CPS

  • Kan, Zhe;Wang, Xiaolei
    • Journal of Information Processing Systems
    • /
    • v.15 no.3
    • /
    • pp.632-644
    • /
    • 2019
  • The remote monitoring and warning system for dangerous chemicals is designed with the concept of the Cyber-Physical System (CPS) in this paper. The real-time perception, dynamic control, and information service of major hazards chemicals are realized in this CPS system. The CPS system architecture, the physical layer and the applacation layer, are designed in this paper. The terminal node is mainly composed of the field collectors which complete the data acquisition of sensors and video in the physical layers, and the use of application layer makes CPS system safer and more reliable to monitor the hazardous chemicals. The cloud application layer completes the risk identification and the prediction of the major hazard sources. The early intelligent warning of the major dangerous chemicals is realized and the security risk images are given in the cloud application layer. With the CPS technology, the remote network of hazardous chemicals has been completed, and a major hazard monitoring and accident warning online system is formed. Through the experiment of the terminal node, it can be proved that the terminal node can complete the mass data collection and classify. With this experiment it can be obtained the CPS system is safe and effective. In order to verify feasible, the multi-risk warning based on CPS is simulated, and results show that the system solves the problem of hazardous chemicals enterprises safety management.

Research Trends Analysis of Big Data: Focused on the Topic Modeling (빅데이터 연구동향 분석: 토픽 모델링을 중심으로)

  • Park, Jongsoon;Kim, Changsik
    • Journal of Korea Society of Digital Industry and Information Management
    • /
    • v.15 no.1
    • /
    • pp.1-7
    • /
    • 2019
  • The objective of this study is to examine the trends in big data. Research abstracts were extracted from 4,019 articles, published between 1995 and 2018, on Web of Science and were analyzed using topic modeling and time series analysis. The 20 single-term topics that appeared most frequently were as follows: model, technology, algorithm, problem, performance, network, framework, analytics, management, process, value, user, knowledge, dataset, resource, service, cloud, storage, business, and health. The 20 multi-term topics were as follows: sense technology architecture (T10), decision system (T18), classification algorithm (T03), data analytics (T17), system performance (T09), data science (T06), distribution method (T20), service dataset (T19), network communication (T05), customer & business (T16), cloud computing (T02), health care (T14), smart city (T11), patient & disease (T04), privacy & security (T08), research design (T01), social media (T12), student & education (T13), energy consumption (T07), supply chain management (T15). The time series data indicated that the 40 single-term topics and multi-term topics were hot topics. This study provides suggestions for future research.

A Multi-Scale Parallel Convolutional Neural Network Based Intelligent Human Identification Using Face Information

  • Li, Chen;Liang, Mengti;Song, Wei;Xiao, Ke
    • Journal of Information Processing Systems
    • /
    • v.14 no.6
    • /
    • pp.1494-1507
    • /
    • 2018
  • Intelligent human identification using face information has been the research hotspot ranging from Internet of Things (IoT) application, intelligent self-service bank, intelligent surveillance to public safety and intelligent access control. Since 2D face images are usually captured from a long distance in an unconstrained environment, to fully exploit this advantage and make human recognition appropriate for wider intelligent applications with higher security and convenience, the key difficulties here include gray scale change caused by illumination variance, occlusion caused by glasses, hair or scarf, self-occlusion and deformation caused by pose or expression variation. To conquer these, many solutions have been proposed. However, most of them only improve recognition performance under one influence factor, which still cannot meet the real face recognition scenario. In this paper we propose a multi-scale parallel convolutional neural network architecture to extract deep robust facial features with high discriminative ability. Abundant experiments are conducted on CMU-PIE, extended FERET and AR database. And the experiment results show that the proposed algorithm exhibits excellent discriminative ability compared with other existing algorithms.

Exploring the dynamic knowledge structure of studies on the Internet of things: Keyword analysis

  • Yoon, Young Seog;Zo, Hangjung;Choi, Munkee;Lee, Donghyun;Lee, Hyun-woo
    • ETRI Journal
    • /
    • v.40 no.6
    • /
    • pp.745-758
    • /
    • 2018
  • A wide range of studies in various disciplines has focused on the Internet of Things (IoT) and cyber-physical systems (CPS). However, it is necessary to summarize the current status and to establish future directions because each study has its own individual goals independent of the completion of all IoT applications. The absence of a comprehensive understanding of IoT and CPS has disrupted an efficient resource allocation. To assess changes in the knowledge structure and emerging technologies, this study explores the dynamic research trends in IoT by analyzing bibliographic data. We retrieved 54,237 keywords in 12,600 IoT studies from the Scopus database, and conducted keyword frequency, co-occurrence, and growth-rate analyses. The analysis results reveal how IoT technologies have been developed and how they are connected to each other. We also show that such technologies have diverged and converged simultaneously, and that the emerging keywords of trust, smart home, cloud, authentication, context-aware, and big data have been extracted. We also unveil that the CPS is directly involved in network, security, management, cloud, big data, system, industry, architecture, and the Internet.