• Proceedings of the Korea Contents Association Conference
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• 2014.11a
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• pp.263-264
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• 2014

공간에 대한 정보는 시간과 함께 사람이 생활을 하는데 있어 반드시 알아야 하는 가장 근본적인 정보이며, 공간정보는 우리가 일상생활이나 특정한 상황에 처해 있을 때 행동이나 태도를 결정하는 중요한 기초정보와 기준을 제시한다. 미래의 공간정보사회에서는 지능 사물이 공간정보를 이용하고 인간은 간접적으로 활용하는 서비스로 진화한다. 미래의 공간정보는 상황정보, 실시간성, 다양성(풍부성), 정밀성을 바탕으로 빅데이터와 클라우드 기술이 융합되어 사용자 중심의 맞춤형 서비스가 제공될 것이다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.55-57
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• 2018

In Simultaneous Localization and Mapping (SLAM), the robot acquire its map of environment while simultaneously localize itself relative to the map. Now a day, a map acquired by the mobile robots limit to specific area, in an indoor environment and cannot able to navigate autonomous between different floors. We propose a design that could able to overcome this issue in order to navigate multiple floors with one end goal mission to a target destination in the course of autonomous navigation. In this research, we consider all the floors have identical structural arrangement. Internet of Things (IoT) playing crucial role in bridging between "things" and Robot Operating System (ROS) enabled mobile robots.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.138-140
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• 2020

As the IoT is applied to home and industrial networks, data generated by the IoT is being processed at the cloud edge. Intrusion detection function is very important because it can be operated by invading IoT devices through the cloud edge. Data delivered to the edge network in the cloud environment is traffic at the application layer. In order to determine the intrusion of the packet transmitted to the IoT, the intrusion should be detected at the application layer. This paper proposes the intrusion detection function at the application layer excluding normal traffic from IoT intrusion detection function. As the proposed method, we obtained the intrusion detection result by decision tree method and explained the detection result for each feature.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.110-113
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• 2022

인터넷을 통해 주위 사물과 연결된 차량은 사용자에게 편리성을 제공하기 위해 다양한 콘텐츠를 요구하는데 클라우드로부터 가져오는 시간이 비교적 오래 걸리기 때문에 차량과 물리적으로 가까운 위치에 캐싱하는 기법들이 등장하고 있다. 본 논문에서는 기반 시설이 밀집하게 설치된 도시 환경에서 maximum distance separable(MDS) 코딩을 사용해 road side unit(RSU)에 캐싱하는 방법에 대해 연구하였다. RSU의 중복된 서비스 커버리지 지역을 고려하여 차량의 콘텐츠 요구에 대한 RSU hit ratio를 높이기 위해 deep Q-learning(DQN)를 사용하였다. 실험 결과 비교 알고리즘보다 hit raito 측면에서 더 높은 성능을 보이는 것을 증명하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.111-112
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• 2021

로봇은 인공지능(AI) 기술을 비롯해 빅데이터, 센서기술, 클라우드 등 다양한 신 분야의 축적된 기술력과 노하우를 필요로 한다. 코로나 19 여파로 비대면 서비스에 대한 수요가 증가하고 정보통신기술이 발전되고 있는 가운데 청소용, 잔디 깎기, 가사용, 동반자, 엔터테인먼트 및 레저용, 노약자 및 장애인 지원 로봇 등 우리생활 주변에서도 서비스 로봇이 빠르게 도입되고 있다. 본 논문에서는 최근 3년간(2018.1~2020.12) 중앙지, 경제지 등 54개 언론사 기사를 빅카인즈와 데이터랩을 이용하여 서비스 로봇&인공지능을 키워드로 관계도 분석, 키워드 트렌드, 연관어 분석을 하였다. 연관어 키워드 빈도수로는 인공지능(534), LG전자(157), 드론(112), 자율주행(101), 빅데이터(81), 로보티즈(61), 사물인터넷(34) 순으로 서비스 로봇의 성장은 인공지능을 비롯한 4차 산업혁명 관련 기술과 연관성이 매우 컸다. 2016년~2020년 기간에 산업용 로봇은 1.89배 증가했으며, 서비스 로봇은 5.21배 증가하여 서비스 로봇의 수요가 다양한 분야에서 확산됨을 확인할 수 있었다.

• Journal of Digital Convergence
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• v.18 no.10
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• pp.233-238
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• 2020

In the cloud environment, IoT devices using sensors and wearable devices are being applied in various environments, and technologies that accurately determine the information generated by IoT devices are being actively studied. However, due to limitations in the IoT environment such as power and security, information generated by IoT devices is very weak, so financial damage and human casualties are increasing. To accurately collect and analyze IoT information, this paper proposes a topographic information-based key management technique that considers IoT information errors. The proposed technique allows IoT layout errors and groups topographic information into groups of dogs in order to secure connectivity of IoT devices in the event of arbitrary deployment of IoT devices in the cloud environment. In particular, each grouped terrain information is assigned random selected keys from the entire key pool, and the key of the terrain information contained in the IoT information and the probability-high key values are secured with the connectivity of the IoT device. In particular, the proposed technique can reduce information errors about IoT devices because the key of IoT terrain information is extracted by seed using probabilistic deep learning.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.89-92
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• 2020

According to the various IoT(Internet of Things) services, there have been lots of task offloading researches for IoT devices. Since there are service response delay and core network load issues in conventional cloud computing based offloadings, fog computing based offloading has been focused whose location is close to the IoT devices. However, even in the fog computing architecture, the load can be concentrated on the for computing node when the number of requests increase. To solve this problem, the opportunistic fog computing concept which offloads task to available computing resources such as cars and drones is introduced. In previous fog and opportunistic fog node researches, the offloading is performed immediately whenever the service request occurs. This means that the service requests can be offloaded to the opportunistic fog nodes only while they are available. However, if the service response delay requirement is satisfied, there is no need to offload the request immediately. In addition, the load can be distributed by making the best use of the opportunistic fog nodes. Therefore, this paper proposes a delayed offloading scheme to satisfy the response delay requirements and offload the request to the opportunistic fog nodes as efficiently as possible.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.18-23
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• 2016

Internet of things (IoT) is revolutionizing in the patient-Centered medical monitoring and management by authorizing the Smartphone application and data analysis with medical centers. The network connectivity is basic requirement to collect the observed human beings' health information from Smartphone to monitor the health from IoT medical devices in personal healthcare. The IoT environment built in Smartphone is very effective and does not demand infrastructure. This paper presents the smart phone deployed personal IoT architecture for Non-Invasive ECG Capturing. The adaptable IoT medical device cum Gateway is used for personal healthcare with big data storage on cloud configuration. In this approach, the Smartphone camera based imaging technique used to extract the personal ECG waveform and forward it to the cloud based big data storage connectivity using IoT architecture. Elaborated algorithm allows for efficient ECG registration directly from face image captured from Smartphone or Tablet camera. The profound technique may have an exceptional value in monitoring personal healthcare after adequate enhancements are introduced.

• Journal of the Korea Convergence Society
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• v.9 no.5
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• pp.27-32
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• 2018

IoT technology is developing with various application areas in $4^{th}$ Industrial revolution. There are many users using the application services. Sensing data from various environment need to be transferred to cloud computing storage and store in the cloud storage. However, physical distance from the end node to cloud computing storage is far away, and it is not efficient to transfer data from sensors and store the sensing data in the cloud storage whenever sensing data happen. Therefore, Fog computing is proposed to solve these problems which can process and store the sensing data. However, Fog computing is new emerging technology, there is no standard security model and requirements. This research proposes to security requirements and security model for Fog computing to establish a secure and efficient cloud computing environment.