• Journal of KIISE
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• v.43 no.6
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• pp.710-717
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• 2016

Recently, several research studies on things abstraction framework have been proposed in order to implement the multi-service Internet of Things (IoT) system, where various IoT services share the thing devices. Distributed things abstraction has an IoT service duplication problem, which aggravates power consumption of mobile devices and network traffic. On the other hand, cloud server-centric things abstraction cannot cover real-time interactions due to long network delay. Fog server-centric things abstraction has limits in insufficient IoT interfaces. In this paper, we propose Smart Fog which is a fog server-centric things abstraction framework to resolve the problems of the existing things abstraction frameworks. Smart Fog consists of software modules to operate the Smart Gateway and three interfaces. Smart Fog is implemented based on IoTivity framework and OIC standard. We construct a smart home prototype on an embedded board Odroid-XU3 using Smart Fog. We evaluate the network performance and energy efficiency of Smart Fog. The experimental results indicate that the Smart Fog shows short network latency, which can perform real-time interaction. The results also show that the proposed framework has reduction in the network traffic of 74% and power consumption of 21% in mobile device, compared to distributed things abstraction.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.454-455
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• 2019

본 논문에서는 표준 기반 사물인터넷 (IoT: Internet of Things) 플랫폼을 활용한 음성 제어 시스템을 구현하고 그 성능을 검증한다. 사물인터넷 산업 표준인 원엠투엠 (oneM2M) 오픈 소스 플랫폼을 활용하여 음성으로 댁내 기기를 제어할 수 있는 프로토타입 시스템을 구현하였다. 음성 기반 제어를 위해 구글의 Speech-to-Text API를 활용하고 오픈 소스 하드웨어에 원엠투엠 플랫폼을 탑재하여 어디서든지 서버 플랫폼에 연결된 댁내 가전기기들을 제어할 수 있음을 보였다. 본 논문에서 구현한 시스템을 통해 표준화된 오픈 소스 플랫폼과 클라우드 음성 인식 API를 활용하여 확장성과 연결성을 갖춘 커넥티드 홈을 구현할 수 있음을 알 수 있다.

• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.140-145
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• 2019

With the development of IT technology, many changes are taking place in the health service environment over the past. However, even if medical technology is converged with IT technology, the problem of medical costs and management of health services are still one of the things that needs to be addressed. In this paper, we propose a model for hospitals that have established the IoT system to efficiently analyze and manage the personal information of users who receive medical services. The proposed model aims to efficiently check and manage users' medical information through an in-house IoT system. The proposed model can be used in a variety of heterogeneous cloud environments, and users' medical information can be managed efficiently and quickly without additional human and physical resources. In particular, because users' medical information collected in the proposed model is stored on servers through the IoT gateway, medical staff can analyze users' medical information accurately regardless of time and place. As a result of performance evaluation, the proposed model achieved 19.6% improvement in the efficiency of health care services for occupational health care staff over traditional medical system models that did not use the IoT system, and 22.1% improvement in post-health care for users who received medical services. In addition, the burden on medical staff was 17.6 percent lower on average than the existing medical system models.

• Journal of Internet Computing and Services
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• v.18 no.2
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• pp.21-30
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• 2017

IoT(Internet of Things) can enable networking and computing using any devices is rapidly proliferated. In the existing IoT environment, bottlenecks and service delays can occur because it processes data and provides services to users using central processing based on Cloud. For this reason, Edge Computing processes data directly in IoT nodes and networks to provide the services to the users has attracted attention. Also, numerous researchers have been attracted to intelligent service efficiently based on Edge Computing. In this paper, expert system-based context awareness scheme for Edge Computing in IoT environment is proposed. The proposed scheme can provide customized services to the users using context awareness and process data in real-time using the expert system based on efficient cooperations of resource limited IoT nodes. The context awareness services can be modified by the users according to the usage purpose. The three service modes in the security system based on smart home are used to test the proposed scheme and the stability of the proposed scheme is proven by a comparison of the resource consumptions of the servers between the proposed scheme and the PC-based expert system.

• Convergence Security Journal
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• v.22 no.1
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• pp.71-79
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• 2022

The smart grid system has emerged to maximize energy efficiency through real-time information exchange between power providers and consumers by combining information technology and power supply systems. The authentication schemes using blockchain in a smart grid system have been proposed, which utilize an edge server's architecture to collect and store electric power-related information and process data between a central cloud server and smart grid-IoT devices. Although authentication schemes are being proposed to enhance security in the smart grid environment, many vulnerabilities are still reported. This paper presents a new mutual authentication scheme to guarantee users' privacy and anonymity in a smart grid based on edge computing using blockchain. In the proposed scheme, we use the smart contract for the key management's efficiency, such as updating and discarding key materials. Finally, we prove that the proposed scheme not only securely establishes a session key between the smart grid-IoT device of the user and the edge server but also guarantees anonymity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.523-535
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• 2017

Local intelligent services aim at controlling local services such as cooling or lightening services in a certain local area, using Internet-of-Things (IoT) sensor data in the area. As the IoT paradigm has evolved, local intelligent services have gained increasing attention. However, most of the local intelligent service mechanism proposed so far do not directly take the users' presence and service preference information into account for controlling local services. This study proposes an individual presence-and-preference-based local service system (IPP-LISS). We present a intelligent service control algorithm and implement a prototype system of IPP-LISS. Typically, the intelligence part of IPP-LISS including the prediction models, is generated on remote server in the cloud because of their compute-intense aspect. However, this can cause huge data traffic between IoT devices and servers in the cloud. The emerging mobile edge computing technology will be a promising solution of this challenge of IPP-LISS. In this paper, we implement IPP-LISS in the cloud, and then, based on the implementation result, we discuss applying the mobile edge computing technology to the IPP-LISS application.

• Journal of Industrial Convergence
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• v.20 no.8
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• pp.61-67
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• 2022

The Internet of Things(IoT) is one of the key technologies in the Fourth Industrial Revolution. The IoT is a system that acquires information from various sensors and provides meaningful information to users. The method of obtaining information from sensor is using WIFI, Bluetooth and Server. is not accessible to external users because of different type of networks or local area communication. For this reason, there is a problem that external user cannot receive notification in regard to sensor information. In this paper, we want to establish a cloud message environment using Google's FCM(Firebase Cloud Messaging) and find out through experiments how users can receive notifications even if they are outside.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.613-621
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• 2019

Recently, with the development of the Internet of Things (IoT) and cloud computing technologies, security threats have increased as malicious codes infect IoT devices, and new malware spreads ransomware to cloud servers. In this study, we propose a threat-detection technique that checks obfuscated script patterns to compensate for the shortcomings of conventional signature-based and behavior-based detection methods. Proposed is a malicious code-detection technique that is based on malicious script-pattern analysis that can detect zero-day attacks while maintaining the existing detection rate by registering and checking derived distribution patterns after analyzing the types of malicious scripts distributed through websites. To verify the performance of the proposed technique, a prototype system was developed to collect a total of 390 malicious websites and experiment with 10 major malicious script-distribution patterns derived from analysis. The technique showed an average detection rate of about 86% of all items, while maintaining the existing detection speed based on the detection rule and also detecting zero-day attacks.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.26 no.5
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• pp.61-68
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• 2021

In this paper, we propose an edge computing-based exercise data collection device that can be provided for exercise rehabilitation services. In the existing cloud computing method, when the number of users increases, the throughput of the data center increases, causing a lot of delay. In this paper, we design and implement a device that measures and estimates the position of keypoints of body joints for movement information collected by a 3D camera from the user's side using edge computing and transmits them to the server. This can build a seamless information collection environment without load on the cloud system. The results of this study can be utilized in a personalized rehabilitation exercise coaching system through IoT and edge computing technologies for various users who want exercise rehabilitation.