• Title/Summary/Keyword: 스마트 워크

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Measurements on Legislation of User-Protection Act in the Era of ICT-Convergence (ICT융합에 따른 방송통신 이용자보호 법제의 합리적 개선방안)

  • Park, Jong-Su
    • Journal of Legislation Research
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    • no.44
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    • pp.103-153
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    • 2013
  • This article aims at the legislation of User-Protection Act in area of ICT. In these days telecommunication and broadcasting are getting more and more convergent. The paradigm of ICT is turning over from the service provider to the end-user. User protection has been in each erea of ICT (C-P-N-D) individually regulated. In the area of telecommunication it is important to protect the interest of user, who stands in contract with the service provider. And in area of broadcasting it is important to protect the interest of viewers, who stands "gratis" with the broadcasters without any contracts. For the more efficient user-protection it is also necessary to make a dedicated organization under KCC(Korean Communications Committee). In this early year the government organization was divided into MSIP(Ministry of Science, ICT and future planing) and KCC. The user-protection act will be very important instrument of ICT regulation in the era of creative economy. It is necessary to establish a new frame act of user protection. It is also necessary to make start to establish a new system of user education in erea of ICT. It is strongly expected the new act will be a turning point of ICT development in Korea.

A Study on Security Requirements for 5G Base Station (5G 기지국에 대한 보안성평가기준 연구)

  • Hong, Paul;Kim, Yejun;Cho, Kwangsoo;Kim, Seungjoo
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.31 no.5
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    • pp.919-939
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    • 2021
  • As a next-generation communication technology, 5G networks are capable of handling large amounts of traffic based on higher speeds, shorter communication delays, and higher connectivity compared to 4G networks. In this 5G network environment, base stations are installed all over the city at high density due to their characteristics, and are connected to user terminals to provide services. Therefore, if the base station is damaged by a malicious attacker, it is expected to cause great damage to users and society as a whole. So the need for secure communication equipment such as 5G base stations has emerged. Therefore, in this paper, we propose the security functional requirements derived using threat modeling, a systematic methodology for 5G base stations, and the security assurance requirements at the level that can cope with the backdoor issues. The security requirements proposed in this paper can be used for base station design and development to construct a secure network environment as a security evaluation standard for 5G base stations.

Distributed Trust Management for Fog Based IoT Environment (포그 기반 IoT 환경의 분산 신뢰 관리 시스템)

  • Oh, Jungmin;Kim, Seungjoo
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.31 no.4
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    • pp.731-751
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    • 2021
  • The Internet of Things is a huge group of devices communicating each other and the interconnection of objects in the network is a basic requirement. Choosing a reliable device is critical because malicious devices can compromise networks and services. However, it is difficult to create a trust management model due to the mobility and resource constraints of IoT devices. For the centralized approach, there are issues of single point of failure and resource expansion and for the distributed approach, it allows to expand network without additional equipment by interconnecting each other, but it has limitations in data exchange and storage with limited resources and is difficult to ensure consistency. Recently, trust management models using fog nodes and blockchain have been proposed. However, blockchain has problems of low throughput and delay. Therefore, in this paper, a trust management model for selecting reliable devices in a fog-based IoT environment is proposed by applying IOTA, a blockchain technology for the Internet of Things. In this model, Directed Acyclic Graph-based ledger structure manages trust data without falsification and improves the low throughput and scalability problems of blockchain.

Development of a deep-learning based automatic tracking of moving vehicles and incident detection processes on tunnels (딥러닝 기반 터널 내 이동체 자동 추적 및 유고상황 자동 감지 프로세스 개발)

  • Lee, Kyu Beom;Shin, Hyu Soung;Kim, Dong Gyu
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.20 no.6
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    • pp.1161-1175
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    • 2018
  • An unexpected event could be easily followed by a large secondary accident due to the limitation in sight of drivers in road tunnels. Therefore, a series of automated incident detection systems have been under operation, which, however, appear in very low detection rates due to very low image qualities on CCTVs in tunnels. In order to overcome that limit, deep learning based tunnel incident detection system was developed, which already showed high detection rates in November of 2017. However, since the object detection process could deal with only still images, moving direction and speed of moving vehicles could not be identified. Furthermore it was hard to detect stopping and reverse the status of moving vehicles. Therefore, apart from the object detection, an object tracking method has been introduced and combined with the detection algorithm to track the moving vehicles. Also, stopping-reverse discrimination algorithm was proposed, thereby implementing into the combined incident detection processes. Each performance on detection of stopping, reverse driving and fire incident state were evaluated with showing 100% detection rate. But the detection for 'person' object appears relatively low success rate to 78.5%. Nevertheless, it is believed that the enlarged richness of image big-data could dramatically enhance the detection capacity of the automatic incident detection system.

The Analysis of the Relationship between the Review Scale and Posting Information of Company and Purchasing Patterns -Focusing on Amazon and Google Users (기업의 리뷰척도 및 포스팅 정보와 구매패턴과의 관계분석 -아마존 구글 유저를 중심으로)

  • Kim, Dong-Il;Choi, Seung-Il
    • Journal of the Korea Convergence Society
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    • v.10 no.10
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    • pp.153-160
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    • 2019
  • In this study, The purpose of this study is to analyze how the rating scale and review contents attributes of social network-based services and products affect consumer purchasing patterns. information provided by screening the main factors. These analyzes are closely and quickly integrated between individuals and businesses, and enable to analyze the transaction that the impact of changing consumers on consumption and purchasing through the usefulness and a priori estimates of reviews and ratings at this time when networks and smart technologies are involved in a wide range of consumer activities. For this study, hierarchical analysis (AHP) and delphi (Delphi) methods applied to classify the high end variables into usefulness, technicality and value, Each subvariable was grouped into three factors and analyzed for importance through evaluation weights. As a result, we could analyze the importance of durability, usefulness, technological innovation, and cost and quality of value. Therefore, this study is expected to provide supplementary and additional useful information to consumers and companies participating in economic activities in various ways by simultaneously analyzing the review score and the reliability of posting information provided by verifying the main factors.

A Novel Reference Model for Cloud Manufacturing CPS Platform Based on oneM2M Standard (제조 클라우드 CPS를 위한 oneM2M 기반의 플랫폼 참조 모델)

  • Yun, Seongjin;Kim, Hanjin;Shin, Hyeonyeop;Chin, Hoe Seung;Kim, Won-Tae
    • KIPS Transactions on Computer and Communication Systems
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    • v.8 no.2
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    • pp.41-56
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    • 2019
  • Cloud manufacturing is a new concept of manufacturing process that works like a single factory with connected multiple factories. The cloud manufacturing system is a kind of large-scale CPS that produces products through the collaboration of distributed manufacturing facilities based on technologies such as cloud computing, IoT, and virtualization. It utilizes diverse and distributed facilities based on centralized information systems, which allows flexible composition user-centric and service-oriented large-scale systems. However, the cloud manufacturing system is composed of a large number of highly heterogeneous subsystems. It has difficulties in interconnection, data exchange, information processing, and system verification for system construction. In this paper, we derive the user requirements of various aspects of the cloud manufacturing system, such as functional, human, trustworthiness, timing, data and composition, based on the CPS Framework, which is the analysis methodology for CPS. Next, by analyzing the user requirements we define the system requirements including scalability, composability, interactivity, dependability, timing, interoperability and intelligence. We map the defined CPS system requirements to the requirements of oneM2M, which is the platform standard for IoT, so that the support of the system requirements at the level of the IoT platform is verified through Mobius, which is the implementation of oneM2M standard. Analyzing the verification result, finally, we propose a large-scale cloud manufacturing platform based on oneM2M that can meet the cloud manufacturing requirements to support the overall features of the Cloud Manufacturing CPS with dependability.

Development of Real-time Video Surveillance System Using the Intelligent Behavior Recognition Technique (지능형 행동인식 기술을 이용한 실시간 동영상 감시 시스템 개발)

  • Chang, Jae-Young;Hong, Sung-Mun;Son, Damy;Yoo, Hojin;Ahn, Hyoung-Woo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.2
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    • pp.161-168
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    • 2019
  • Recently, video equipments such as CCTV, which is spreading rapidly, is being used as a means to monitor and cope with abnormal situations in almost governments, companies, and households. However, in most cases, since recognizing the abnormal situation is carried out by the monitoring person, the immediate response is difficult and is used only for post-analysis. In this paper, we present the results of the development of video surveillance system that automatically recognizing the abnormal situations and sending such events to the smartphone immediately using the latest deep learning technology. The proposed system extracts skeletons from the human objects in real time using Openpose library and then recognizes the human behaviors automatically using deep learning technology. To this end, we reconstruct Openpose library, which developed in the Caffe framework, on Darknet framework to improve real-time processing. We also verified the performance improvement through experiments. The system to be introduced in this paper has accurate and fast behavioral recognition performance and scalability, so it is expected that it can be used for video surveillance systems for various applications.

An Implementation of an Intelligent Access Point System Based on a Feed Forward Neural Network for Internet of Things (사물인터넷을 위한 신경망 기반의 지능형 액세스 포인트 시스템의 구현)

  • Lee, Youngchan;Lee, SoYeon;Kim, Dae-Young
    • Journal of Internet Computing and Services
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    • v.20 no.5
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    • pp.95-104
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    • 2019
  • Various kinds of devices are used for the Internet of Things (IoT) service, and IoT devices mainly use communication technology that uses the frequency of the unlicensed band. There are several types of communication technology in the unlicensed band, but WiFi is most commonly used. Devices used for IoT services vary in computing resources from devices with limited capabilities to smartphones and provide services over wireless networks such as WiFi. Most IoT devices can't perform complex operations for network control, thus they choose a WiFi access point (AP) based on signal strength. This causes a decrease in IoT service efficiency. In this paper, an intelligent AP system that can efficiently control the WiFi connection of the IoT devices is implemented. Based on the network information measured by the IoT device, the access point learns using a feed forward neural network algorithm, and predicts a network connection state to control the WiFi connection. By controlling the WiFi connection at the AP, the service efficiency of the IoT device can be improved.

A Study on Geospatial Information Role in Digital Twin (디지털트윈에서 공간정보 역할에 관한 연구)

  • Lee, In-Su
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.3
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    • pp.268-278
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    • 2021
  • Technologies that are leading the fourth industrial revolution, such as the Internet of Things (IoT), big data, artificial intelligence (AI), and cyber-physical systems (CPS) are developing and generalizing. The demand to improve productivity, economy, safety, etc., is spreading in various industrial fields by applying these technologies. Digital twins are attracting attention as an important technology trend to meet demands and is one of the top 10 tasks of the Korean version of the New Deal. In this study, papers, magazines, reports, and other literature were searched using Google. In order to investigate the contribution or role of geospatial information in the digital twin application, the definition of a digital twin, we investigated technology trends of domestic and foreign companies; the components of digital twins required in manufacturing, plants, and smart cities; and the core techniques for driving a digital twin. In addition, the contributing contents of geospatial information were summarized by searching for a sentence or word linked between geospatial-related keywords (i.e., Geospatial Information, Geospatial data, Location, Map, and Geodata and Digital Twin). As a result of the survey, Geospatial information is not only providing a role as a medium connecting objects, things, people, processes, data, and products, but also providing reliable decision-making support, linkage fusion, location information provision, and frameworks. It was found that it can contribute to maximizing the value of utilization of digital twins.

Implementation of A Security Token System using Fingerprint Verification (지문 인증을 이용한 보안 토큰 시스템 구현)

  • 문대성;길연희;안도성;반성범;정용화;정교일
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.13 no.4
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    • pp.63-70
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    • 2003
  • In the modern electronic world, the authentication of a person is an important task in many areas of online-transactions. Using biometrics to authenticate a person's identity has several advantages over the present practices of Personal Identification Numbers(PINs) and passwords. To gain maximum security in the verification system using biometrics, the computation of the verification as well as the store of the biometric pattern has to be taken place in the security token(smart card, USB token). However, there is an open issue of integrating biometrics into the security token because of its limited resources(memory space, processing power). In this paper, we describe our implementation of the USB security token system having 206MHz StrongARM CPU, 16MBytes flash memory, and 1MBytes RAM. Also, we evaluate the performance of a light-weighted In-gerprint verification algorithm that can be executed in the restricted environments. Based on experimental results, we confirmed that the RAM requirement of the proposed algorithm was about 6.8 KBytes and the Equal Error Rate(EER) was 1.7%.