• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.98-100
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• 2023

IoT(Internet of Things) 기기를 활용하는 분야가 증가함에 따라 스마트 팩토리, 스마트 그리드 등 융합환경이 발전되었으며, 융합환경이 상호연결되는 IoBE(Internet of Things Blended Environment)가 조성되고 있다. 그러나, IoBE 구성요소가 복잡해짐에 따라 공격 표면이 증가하고, 기존에 알려진 보안위협이 융·복합되어 새로운 형태의 보안위협인 복합위협(BT, Blended Threat)이 발생할 수 있다. BT는 다양한 보안위협이 복합적으로 연계되어 발생함에 따라 예측하여 대응하기에 기존 보안위협보다 상대적으로 어려우며, 이에 대응방안 간의 조합을 통해 보안위협에 유동적으로 대응하는 동적 보안 프레임워크가 필요하다. 따라서, 본 논문에서는 BT에 대한 대응방안 동적 조합 프레임워크를 제안한다.

• Journal of information and communication convergence engineering
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• v.16 no.1
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• pp.31-37
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• 2018

In this work, we propose an analytic framework for evaluating the quality of service and dimensioning the link capacity in the gateway router of a smart farm with a greenhouse eco-management system. Specifically, we focus on the gateway router of an IoT network that provides an access service for smart farms. We design the link capacity of a gateway router that is used for the remote management of the greenhouse eco-management system to accommodate both time-critical and delay-tolerant traffic in a greenhouse LAN. For this purpose, we first investigate the ecosystem for smart farm, and we define the specification and requirements of the greenhouse eco-management system. Second, we propose a system model for the link capacity of a gateway that is required to guarantee the delay performance of time-critical applications in the greenhouse LAN. Finally, the validity of the proposed system is demonstrated through a series of numerical experiments.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.01a
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• pp.57-58
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• 2017

사물인터넷 환경의 다양한 기기에서는 매초마다 시스템 로그 데이터, 온도, 습도, 조도 및 위치 정보 등과 같은 데이터를 지속적으로 생성한다. 이렇게 생성된 데이터는 기기 안에서 대부분 소멸되거나 수집된다 하더라도 시스템 개선의 일부 목적으로 활용하는데 그칠 뿐이다. 본 논문에서는 각각의 사물인터넷 기기에서 발생하는 비정형 데이터를 스트리밍 방식을 통해 수집 서버로 전송하고 이를 유연한 스키마 구조를 가지는 NoSQL 데이터베이스에 적재하는 프레임워크 설계를 제안한다. 이렇게 수많은 장비로부터 수집된 로그 및 센싱 데이터는 빅데이터 분석을 통해 산업의 현장에서 생산성 향상을 위해 사용할 수 있으며 공공의 목적으로 도심지의 교통문제 해소와 재난 및 재해 예측에 활용될 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.839-842
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• 2016

최근 사물인터넷에 대한 관심과 투자가 크게 증가하고 있으나 보안 측면에서 문제가 지속적으로 제기되고 있다. 그 해결책으로서 기업에서는 기업 내에서 구현한 클라이언트와 서버들로만 구성되어진 자체 IoT 생태계를 구축하고 있다. 그러나 이러한 방식의 단점으로는 다양한 서드파티 어플리케이션이 해당 IoT 서버들의 자원을 활용할 수 없다는 것이다. 따라서 본 논문에서는 이를 보안한 OAuth 2.0 기반 CoAP 인증 프레임워크의 설계를 제안한다.

• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.4
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• pp.49-59
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• 2017

Smart sensing plays a key role in a variety of IoT applications, and its importance is growing more and more together with the development of artificial intelligence. Therefore the importance of smart sensors cannot be overemphasized. However, most studies related to smart sensors have been focusing on specific application purposes, for example, security, energy saving, monitoring, and there are not much effort on researches on how to efficiently configure various types of smart sensors to be needed in the future. In this paper, a component-based framework with hierarchical structure for efficient construction of smart sensor is proposed and its application to smart home is designed and implemented. The proposed method shows that various types of smart sensors to be appeared in the near future can be configured through the design and development of necessary components within the proposed software framework. In addition, since it has a layered architecture, the configuration of the smart sensor can be expanded by inserting the internal or external layers. In particular, it is possible to independently design the internal and external modules when designing an IoT application service through connection with the external device layer. A small-scale smart home system is designed and implemented using the proposed method, and a home cloud operating as an external layer, is further designed to accommodate and manage multiple smart homes. By developing and thus adding the components of each layer, it will be possible to efficiently extend the range of applications such as smart cars, smart buildings, smart factories an so on.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.97-110
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• 2022

Federated learning is a learning method capable of performing model learning without transmitting learning data. The IoT or healthcare field is sensitive to information leakage as it deals with users' personal information, so a lot of attention should be paid to system design, but when using federated-learning, data does not move from devices where data is collected. Accordingly, many federated-learning implementations have been developed, but detailed research on system design for the development and operation of systems using federated learning is insufficient. This study shows that measures for the life cycle, code version management, model serving, and device monitoring of federated learning are needed to be applied to actual projects and distributed to IoT devices, and we propose a design for a development environment that complements these points. The system proposed in this paper considered uninterrupted model-serving and includes source code and model version management, device state monitoring, and server-client learning schedule management.

• Smart Media Journal
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• v.11 no.2
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• pp.70-76
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• 2022

IoT application development using a cloud server causes problems such as data transmission and reception delay, network traffic, and cost for real-time processing support in network connected hardware. To solve this problem, edge cloud-based platforms can use neuromorphic hardware to enable fast data transfer. In this paper, we propose a model optimization method for supporting spiking neural networks on FPGA hardware. We focused on auto-adjusting network model parameters optimized for neuromorphic hardware. The proposed method performs optimization to show higher performance based on user requirements for accuracy. As a result of performance analysis, it satisfies all requirements of accuracy and showed higher performance in terms of expected execution time, unlike the naive method supported by the existing open source framework.

• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.315-322
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• 2023

Intelligent IoT environments that accommodate a very large number of clients require technologies that provide secure information service regardless of the number of clients. Wireless data broadcast is an information service technique that ensures scalability to deliver data to all clients simultaneously regardless of the number of clients. In wireless data broadcasting, clients access the wireless channel linearly to explore the data, so the access time of clients is greatly affected by the broadcast cycle. Data compression-based data broadcasting can reduce the broadcast cycle and thus reduce client access time. Therefore, a simulation framework that can evaluate the performance of data broadcasting by applying different data compression algorithms is essential and important. In this paper, we propose a simulation framework to evaluate the performance of data broadcasting that can adopt data compression. We design the framework that enables to apply different data compression algorithms according to the data characteristics. In addition to evaluating the performance according to the data, the proposed framework can also evaluate the performance according to the data scheduling technique and the kind of queries the client wants to process. We implement the proposed framework and evaluate the performance of data broadcasting using the framework applying data compression algorithms to demonstrate the performances of data compression broadcasting.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.2
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• pp.241-250
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• 2017

Contrary to past critical infrastructure network, current critical infrastructure network is adopting IoT devices and efficient management system using the external networks. Using this system, productivity and management efficiency could be enhanced compared to past critical infrastructure network. But cybersecurity issue could be occurred at external network connection, so cybersecurity guideline is necessary. However, critical infrastructure organizations tend to use the cybersecurity guideline issued by government because it is hard to develop cybersecurity guideline on their own. But the government's cybersecurity guideline isn't suitable for the critical infrastructure network because it doesn't include critical infrastructure's specific characteristics. Therefor, we suggested the development method of cybersecurity guideline for the critical infrastructure network based on analysing cybersecurity guideline standards and critical infrastructure networks.