• 제목/요약/키워드: 스마트워크환경

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Data processing techniques applying data mining based on enterprise cloud computing (데이터 마이닝을 적용한 기업형 클라우드 컴퓨팅 기반 데이터 처리 기법)

  • Kang, In-Seong;Kim, Tae-Ho;Lee, Hong-Chul
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.8
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    • pp.1-10
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    • 2011
  • Recently, cloud computing which has provided enabling convenience that users can connect from anywhere and user friendly environment that offers on-demand network access to a shared pool of configurable computing resources such as smart-phones, net-books and PDA etc, is to be watched as a service that leads the digital revolution. Now, when business practices between departments being integrated through a cooperating system such as cloud computing, data streaming between departments is getting enormous and then it is inevitably necessary to find the solution that person in charge and find data they need. In previous studies the clustering simplifies the search process, but in this paper, it applies Hash Function to remove the de-duplicates in large amount of data in business firms. Also, it applies Bayesian Network of data mining for classifying the respect data and presents handling cloud computing based data. This system features improved search performance as well as the results Compared with conventional methods and CPU, Network Bandwidth Usage in such an efficient system performance is achieved.

A Study on Developing Policy Indicators of Personal Information Protection for Expanding Secure Internet of Things Service (안전한 사물인터넷 서비스 확산을 위한 개인정보보호정책평가지표 개발에 관한 연구)

  • Shin, Young-Jin
    • Informatization Policy
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    • v.25 no.3
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    • pp.29-51
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    • 2018
  • As the core technology of the Fourth Industrial Revolution, the Internet of Things has been developed and has enabled various services, and personal information has been handled freely in the process. However, the infringement threat of personal information is increasing as more convenient services are provided and more information devices including smart devices are connected to the network. Therefore, this study is to analyze prioritizing personal information protection policy indicators in order to provide IoT services by constructing secure environment for implementing the Internet of things as the core technology of the 4th Industrial Revolution. This study reviewed personal information protection policy indicators based on the literature survey, and identified 3 fields, 9 areas, and 25 indicators through Delphi analysis for experts. The weights were calculated based on the AHP survey for 66 experts and the results were used to present the relative importance and priority of the policy indexes. The results of this study found the policy field was the most important, followed by the technical field, and the administrative field. Of the three areas of the policy field, strengthening the personal information protection laws related to IoT is the most important, while among the indicators, promoting and revising the personal information protection law related to IoT is the most important. Comparisons of the fields, areas, and indicators of IoT-related personal information protection policies found consistent values. The personal information protection policy indicators derived this way will contribute to the nation's competitiveness by expanding secure IoT policies in the future.

Self-Organizing Middleware Platform Based on Overlay Network for Real-Time Transmission of Mobile Patients Vital Signal Stream (이동 환자 생체신호의 실시간 전달을 위한 오버레이 네트워크 기반 자율군집형 미들웨어 플랫폼)

  • Kang, Ho-Young;Jeong, Seol-Young;Ahn, Cheol-Soo;Park, Yu-Jin;Kang, Soon-Ju
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38C no.7
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    • pp.630-642
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    • 2013
  • To transmit vital signal stream of mobile patients remotely, it requires mobility of patient and watcher, sensing function of patient's abnormal symptom and self-organizing service binding of related computing resources. In the existing relative researches, the vital signal stream is transmitted as a centralized approach which exposure the single point of failure itself and incur data traffic to central server although it is localized service. Self-organizing middleware platform based on heterogenous overlay network is a middleware platform which can transmit real-time data from sensor device(including vital signal measure devices) to Smartphone, TV, PC and external system through overlay network applied self-organizing mechanism. It can transmit and save vital signal stream from sensor device autonomically without arbitration of management server and several receiving devices can simultaneously receive and display through interaction of nodes in real-time.

A Practical Attack on In-Vehicle Network Using Repacked Android Applications (커넥티드 카 환경에서 안드로이드 앱 리패키징을 이용한 자동차 강제 제어 공격)

  • Lee, Jung Ho;Woo, Samuel;Lee, Se Young;Lee, Dong Hoon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.26 no.3
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    • pp.679-691
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    • 2016
  • As vehicle started to contain many different communication devices, collecting external information became possible in IoT environment. In such environment, remotely controling vehicle is possible when vehicle information is obtained by looking in to vehicle network through smart device. However, android based smart device applications are vulnerable to malicious modulation and redistribution. Modulated android application can lead to vehicle information disclosure that could bring about vehicle control accident which becomes threat to drivers. furthermore, since vehicles today does not contain security methods to protect it, they are very vulnerable to security threats which can cause serious damage to users and properties. In this paper, many different vehicle management android applications that are sold in Google Play has been analyzed. With this information, possible threats that could happen in vehicle management applications are being analysed to prove the risks. the experiment is done on actual vehicle to prove the risks. Also, access control method to protect the vehicle against malicious actions that could happen through external network in IoT environment is suggested in the paper.

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.

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.

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%.

A Study on the Utilization of YouTube Platform in Two Traffic Broadcastings (교통방송의 유튜브 플랫폼 활용에 관한 연구)

  • Yoon, Hong Keun
    • The Journal of the Korea Contents Association
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    • v.21 no.12
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    • pp.66-75
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    • 2021
  • The research is centered towards analyzing the usage status of YouTube platform and the nature of content supplied to YouTube by selecting Korean two Traffic Broadcastings Based on TBS(Traffic Broadcasting System) and TBN(Traffic Broadcasting Network). TBS operates 'Citizen's Broadcasting', which has 1.1 million subscribers among 13 YouTube channels, as its main channel. TBN has only 15,000 subscribers to its main 'TBN Tong', and YouTube channels in 12 local networks. TBS which has a dedicated YouTube manpower, is far ahead of TBN in terms of YouTube channel management and content composition. Both broadcasters are passive about creating new media content due to job stability. For the development of the YouTube platform for these two broadcasters, organizational changes within traffic broadcasting and changes in the perception of members are required, and live broadcasting and discovery of star creators are required. In the changing media environment two traffic broadcastings need a program distribution strategy that can be included in various media platforms.

Time series and deep learning prediction study Using container Throughput at Busan Port (부산항 컨테이너 물동량을 이용한 시계열 및 딥러닝 예측연구)

  • Seung-Pil Lee;Hwan-Seong Kim
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.06a
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    • pp.391-393
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    • 2022
  • In recent years, technologies forecasting demand based on deep learning and big data have accelerated the smartification of the field of e-commerce, logistics and distribution areas. In particular, ports, which are the center of global transportation networks and modern intelligent logistics, are rapidly responding to changes in the global economy and port environment caused by the 4th industrial revolution. Port traffic forecasting will have an important impact in various fields such as new port construction, port expansion, and terminal operation. Therefore, the purpose of this study is to compare the time series analysis and deep learning analysis, which are often used for port traffic prediction, and to derive a prediction model suitable for the future container prediction of Busan Port. In addition, external variables related to trade volume changes were selected as correlations and applied to the multivariate deep learning prediction model. As a result, it was found that the LSTM error was low in the single-variable prediction model using only Busan Port container freight volume, and the LSTM error was also low in the multivariate prediction model using external variables.

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