• Title/Summary/Keyword: Artificial cloud

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A Study on the Application of the Cyber Threat Management System to the Future C4I System Based on Big Data/Cloud (빅데이터/클라우드 기반 미래 C4I체계 사이버위협 관리체계 적용 방안 연구)

  • Park, Sangjun;Kang, Jungho
    • Convergence Security Journal
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    • v.20 no.4
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    • pp.27-34
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    • 2020
  • Recently, the fourth industrial revolution technology has not only changed everyday life greatly through technological development, but has also become a major keyword in the establishment of defense policy. In particular, Internet of Things, cloud, big data, mobile and cybersecurity technologies, called ICBMS, were selected as core leading technologies in defense information policy along with artificial intelligence. Amid the growing importance of the fourth industrial revolution technology, research is being carried out to develop the C4I system, which is currently operated separately by the Joint Chiefs of Staff and each military, including the KJCCS, ATCIS, KNCCS and AFCCS, into an integrated system in preparation for future warfare. This is to solve the problem of reduced interoperability for joint operations, such as information exchange, by operating the C4I system for each domain. In addition, systems such as the establishment of an integrated C4I system and the U.S. military's Risk Management Framework (RMF) are essential for efficient control and safe operation of weapons systems as they are being developed into super-connected and super-intelligent systems. Therefore, in this paper, the intelligent cyber threat detection, management of users' access to information, and intelligent management and visualization of cyber threat are presented in the future C4I system based on big data/cloud.

Development Trends of Defense Science and Technology based on the 4th Industrial Revolution (제4차 산업혁명 기반의 국방과학기술 개발 동향)

  • Jeong, Y.H.;Kim, S.N.;Park, H.S.
    • Electronics and Telecommunications Trends
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    • v.35 no.6
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    • pp.56-67
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    • 2020
  • The core technologies of the 4th Industrial Revolution, such as artificial intelligence, the Internet of Things, the cloud, big data, and mobile networks, are inspiring major changes and innovations in the defense sector worldwide. The United States, China, and Russia are pursuing defense research and development strategies that seek to maintain their leadership on the battlefield in the future through the overwhelming superiority of defense science technology. Defense science and technology concentrate on the development of challenging new disruptive technologies to efficiently respond to future battlefield environments, where the immediate process of determining the outcome of a war will lead to combat power. In this paper, we first look at the development strategies of the 4th Industrial Revolution in major countries and describe the latest trends in defense science and technology accordingly.

Smart Service System-based Architecture Design of Smart Factory (스마트 서비스 시스템 기반 스마트 팩토리 아키텍처 설계)

  • Lee, Heeje;Lee, Joongyoon
    • Journal of the Korean Society of Systems Engineering
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    • v.13 no.2
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    • pp.57-64
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    • 2017
  • A new paradigm based on distributed manufacturing services is emerging. This paradigm shift can be realized by smart functions and smart technologies such as Cyber Physical System (CPS), Artificial Intelligence (AI), and Cloud Computing. Most architectures define stack levels from Level 0 (equipment) to Level 4 (business area) and specify the services to be provided between them. Because of their a rough technical specification, there is a limitation on how to actually utilize a technology to actually implement a smart factory service with this architecture. In this paper, we propose a smart factory architecture that can be utilized directly from the perspective of a smart service system by making the use of System Engineering Process and System Modeling Language (SysML).

An Exploratory Study on the Core Technology of the Fourth Industrial Revolution and Information Security Organization: Focusing on Firm Performance (4차산업혁명 핵심기술 도입 및 정보보호조직에 관한 탐색적 연구: 성과측면에서의 비교분석)

  • Kim, Kihyun;Cho, Hyejin;Lim, Sohee
    • Knowledge Management Research
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    • v.21 no.1
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    • pp.41-59
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    • 2020
  • This explorative study examines the difference in firm performance according to the adoption of the core technology of the Fourth industrial revolution, including artificial intelligence(AI), internet of things (IoT), cloud computing, and big data technology. Additionally, we investigate the importance of internal organizational structure exclusively responsible for information security. We analyze unique microdata offered by the Korea Information Society Development Institute to examine the impact of the adoption of the new technologies and the existence of organizational structure for information protection on firm performance, i.e., firm sales. By considering the core information technology as powerful knowledge assets, we argue that the adoption of such technology leads firms to have comparative advantage comparing to the competitors. Also, we emphasize the need to consider the organizational structure suitable for information security, which can become a structural asset of a firm.

Intelligent Energy (지능형 에너지)

  • Oh, D.K.;Ji, H.G.;Kim, Y.H.;Kang, M.K;Choi, B.G;Lee, I.W.;Lee, B.T.;Kim, B.U.;Hong, T.C.;Sung, D.K.
    • Electronics and Telecommunications Trends
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    • v.33 no.4
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    • pp.92-102
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    • 2018
  • On a global level, the energy problem is a very important policy topic, particularly at a time when the nation relies on imports for more than 95% of its energy demand. The starting point of an energy policy should be in line with the international community's concern and cooperation regarding climate warming, and the logic of the new policy on renewable energy expansion in Korea, the pre-developed energy sector, and policy of deserting coal all support this aspect. In particular, to accommodate the rapid urbanization of mankind, the key words of the 4th Industrial Revolution are linking energy to IoT, artificial intelligence, block chain, cloud, and big data.

Trends in Ultra Low Power Intelligent Edge Semiconductor Technology (초저전력 엣지 지능형반도체 기술 동향)

  • Oh, K.I.;Kim, S.E.;Bae, Y.H.;Park, S.M.;Lee, J.J.;Kang, S.W.
    • Electronics and Telecommunications Trends
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    • v.33 no.6
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    • pp.24-33
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    • 2018
  • In the age of IoT, in which everything is connected to a network, there have been increases in the amount of data traffic, latency, and the risk of personal privacy breaches that conventional cloud computing technology cannot cope with. The idea of edge computing has emerged as a solution to these issues, and furthermore, the concept of ultra-low power edge intelligent semiconductors in which the IoT device itself performs intelligent decisions and processes data has been established. The key elements of this function are an intelligent semiconductor based on artificial intelligence, connectivity for the efficient connection of neurons and synapses, and a large-scale spiking neural network simulation framework for the performance prediction of a neural network. This paper covers the current trends in ultra-low power edge intelligent semiconductors including issues regarding their technology and application.

Study on Improving Endpoint Security Technology (엔드포인트 공격대응을 위한 보안기법 연구)

  • Yoo, Seung Jae
    • Convergence Security Journal
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    • v.18 no.3
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    • pp.19-25
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    • 2018
  • Endpoint security is a method of ensuring network security by thoroughly protecting multiple individual devices connected to the network. In this study, we survey the functions and features of various commercial products of endpoint security. Also we emphasizes the importance of endpoint security to respond to the increasingly intelligent and sophisticated security threats against the cloud, mobile, artificial intelligence, and IoT based sur-connection era. and as a way to improve endpoint security, we suggest the ways to improve the life cycle of information security such as preemptive security policy implementation, real-time detection and filtering, detection and modification.

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Learning Algorithms in AI System and Services

  • Jeong, Young-Sik;Park, Jong Hyuk
    • Journal of Information Processing Systems
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    • v.15 no.5
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    • pp.1029-1035
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    • 2019
  • In recent years, artificial intelligence (AI) services have become one of the most essential parts to extend human capabilities in various fields such as face recognition for security, weather prediction, and so on. Various learning algorithms for existing AI services are utilized, such as classification, regression, and deep learning, to increase accuracy and efficiency for humans. Nonetheless, these services face many challenges such as fake news spread on social media, stock selection, and volatility delay in stock prediction systems and inaccurate movie-based recommendation systems. In this paper, various algorithms are presented to mitigate these issues in different systems and services. Convolutional neural network algorithms are used for detecting fake news in Korean language with a Word-Embedded model. It is based on k-clique and data mining and increased accuracy in personalized recommendation-based services stock selection and volatility delay in stock prediction. Other algorithms like multi-level fusion processing address problems of lack of real-time database.

Zero Accident, Connected Autonomous Driving Vehicle (사고제로, 커넥티드 자율이동체)

  • Choi, J.D.;Min, K.W.;Kim, J.H.;Seo, B.S.;Kim, D.H.;Yoo, D.S.;Cho, J.I.
    • Electronics and Telecommunications Trends
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    • v.36 no.1
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    • pp.22-31
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    • 2021
  • In this thesis, we examine the development status of autonomous mobility services using various artificial intelligence algorithms and propose a solution by combining edge and cloud computing to overcome technical difficulties. A fully autonomous vehicle with enhanced safety and ethics can be implemented using the proposed solution. In addition, for the future of 2035, we present a new concept that enables two- and three-dimensional movement via cooperation between ecofriendly, low-noise, and modular fully autonomous vehicles. The zero-error autonomous driving system will safely and conveniently transport people, goods, and services without time and space constraints and contribute to the autonomous mobility services that are free from movement in connection with various mobility.

X-Ray Security Checkpoint System Using Storage Media Detection Method Based on Deep Learning for Information Security

  • Lee, Han-Sung;Kim Kang-San;Kim, Won-Chan;Woo, Tea-Kun;Jung, Se-Hoon
    • Journal of Korea Multimedia Society
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    • v.25 no.10
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    • pp.1433-1447
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    • 2022
  • Recently, as the demand for physical security technology to prevent leakage of technical and business information of companies and public institutions increases, the high tech companies are operating X-ray security checkpoints at building entrances to protect their intellectual property and technology. X-ray security checkpoints are operated to detect cameras and storage media that may store or leak important technologies in the bags of people entering and leaving the building. In this study, we propose an X-ray security checkpoint system that automatically detects a storage medium in an X-ray image using a deep learning based object detection method. The proposed system consists of an edge computing unit and a cloud-computing unit. We employ the RetinaNet for automatic storage media detection in the X-ray security checkpoint images. The proposed approach achieved mAP of 95.92% on private dataset.