• Journal of Digital Convergence
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• v.18 no.3
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• pp.189-194
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• 2020

Recently, various clustering techniques have been studied to efficiently handle data generated by heterogeneous IoT devices. However, existing clustering techniques are not suitable for mobile IoT devices because they focus on statically dividing networks. This paper proposes a probabilistic deep learning-based dynamic clustering model for collecting and analyzing information on IoT devices using edge networks. The proposed model establishes a subnet by applying the frequency of the attribute values collected probabilistically to deep learning. The established subnets are used to group information extracted from seeds into hierarchical structures and improve the speed and accuracy of dynamic clustering for IoT devices. The performance evaluation results showed that the proposed model had an average 13.8 percent improvement in data processing time compared to the existing model, and the server's overhead was 10.5 percent lower on average than the existing model. The accuracy of extracting IoT information from servers has improved by 8.7% on average from previous models.

• Journal of Convergence for Information Technology
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• v.12 no.2
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• pp.23-29
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• 2022

Recently, due to the increase in the use of Internet of Things (IoT) devices, the amount of data transmitted and processed to cloud computing servers has increased rapidly. As a result, network problems (delay, server overload and security threats) are emerging. In particular, edge computing with lower computational capabilities than cloud computing requires a lightweight authentication algorithm that can easily authenticate numerous IoT devices.In this paper, we proposed a key-agreement protocol of a lightweight algorithm that guarantees anonymity and forward and backward secrecy between IoT and edge devices. and the proposed algorithm is stable in MITM and replay attacks for edge device and IoT. As a result of comparing and analyzing the proposed key-agreement protocol with previous studies, it was shown that a lightweight protocol that can be efficiently used in IoT and edge devices.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.37-47
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• 2018

The number of capabilities of Internet of Things (IoT) devices will exponentially grow over the next years. These devices may generate a vast amount of time-constrained data. In the context of IoT, data management should act as a layer between the objects and devices generating the data and the applications accessing the data for analysis purposes and services. In addition, most of IoT services will be content-centric rather than host centric to increase the data availability and the efficiency of data delivery. IoT will enable all the communication devices to be interconnected and make the data generated by or associated with devices or objects globally accessible. Also, fog computing keeps data and computation close to end users at the edge of network, and thus provides a new breed of applications and services to end users with low latency, high bandwidth, and geographically distributed. In this paper, we propose Edge-Fog cloud-based Hierarchical Data Delivery ($EFcHD^2$) method that effectively and reliably delivers IoT data to associated with IoT applications with ensuring time sensitivity. The proposed $EFcHD^2$ method stands on basis of fully decentralized hybrid of Edge and Fog compute cloud model, Edge-Fog cloud, and uses information-centric networking and bloom filters. In addition, it stores the replica of IoT data or the pre-processed feature data by edge node in the appropriate locations of Edge-Fog cloud considering the characteristic of IoT data: locality, size, time sensitivity and popularity. Then, the performance of $EFcHD^2$ method is evaluated through an analytical model, and is compared to fog server-based and Content-Centric Networking (CCN)-based data delivery methods.

• Electronics and Telecommunications Trends
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• v.30 no.1
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• pp.94-101
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• 2015

이동통신 기반 IoT(Internet of Things) 관련 표준들은 3GPP와 ETSI를 중심으로 제정되어 왔으나 2012년부터 표준의 중복을 회피하고 단일화된 표준을 통해서 IoT 시장을 성장시키고자 oneM2M이라는 국제적 협의체가 구성되었으며, 최근 Release 1 표준을 발표하는 등 IoT 표준을 사실상 주도하고 있다. Mason과 Machina 리서치에 따르면 2020년에는 동시 연결된 M2M(Machine to Machine)/IoT 장치들의 수가 21억개에 달할 것이고, 이것들이 동시에 200억개의 통신 연결을 생성할 것이다. 이런 수많은 장치들을 관리하기 위한 표준으로 OMA(Open Mobile Alliance)에서는 LWM2M(Lightweight M2M)를 제정하였다. 또한 이런 장치들은 센서들과 같이 연산능력과 배터리에 제약이 많아서 이것을 극복할 수 있는 메시지 프로토콜로 IETF에서는 CoAP 표준을 제정하였다. oneM2M에서도 CoAP과 LWM2M 표준을 채택하였고, 이를 기반으로 한 단말과 응용서비스 관리 기능이 확대될 것으로 기대된다. 본고에서는 이동통신 기반 IoT 표준 동향과 LWM2M 기반 단말 관리 규격에 대해 살펴본다.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.151-157
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• 2021

Recently, IoT technology has been applied to various cloud environments, requiring accurate verification of various information generated by IoT devices. However, due to the convergence of IoT technologies and 5G technologies, accurate analysis is required as IoT information processing is rapidly processed. This paper proposes a blockchain-based multi-IoT verification model for overlay cloud environments. The proposed model multi-processes IoT information by further classifying IoT information two layers (layer and layer) into bits' blockchain to minimize the bottleneck of overlay networks while ensuring the integrity of information sent and received from embedded IoT devices within local IoT groups. Furthermore, the proposed model allows the layer to contain the weight information, allowing IoT information to be easily processed by the server. In particular, transmission and reception information between IoT devices facilitates server access by distributing IoT information from bits into blockchain to minimize bottlenecks in overlay networks and then weighting IoT information.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.140-146
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• 2021

As the environment using intelligent IoT devices increases, various studies are underway to ensure the integrity of information sent and received from intelligent IoT devices. However, all IoT information generated in heterogeneous environments is not fully provided with reliable protocols and services. In this paper, we propose an intelligent-based multi-blockchain model that can extract only critical information among various information processed by intelligent IoT devices. In the proposed model, blockchain is used to ensure the integrity of IoT information sent and received from IoT devices. The proposed model uses the correlation index of the collected information to trust a large number of IoT information to extract only the information with a high correlation index and bind it with blockchain. This is because the collected information can be extended to the n-tier structure as well as guaranteed reliability. Furthermore, since the proposed model can give weight information to the collection information based on blockchain, similar information can be selected (or bound) according to priority. The proposed model is able to extend the collection information to the n-layer structure while maintaining the data processing cost processed in real time regardless of the number of IoT devices.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1213-1222
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• 2021

This study is a digitalization study based on ICT technology as part of the development of innovative technologies in the new energy industry as a 2050 carbon-neutral policy. It is the development of an oneM2M-based IoT server platform that can be integrated and managed in conjunction with the external interface of each energy facility. It analyzes KEPCO's e-IoT standard specifications through the Power Research Institute's 'SPIN' and develops representative standards, LWM2M and oneM gateway platforms. OneM2M secures and analyzes the recently announced standard for Release 2 instead of the existing Release 1. In addition, the e-IoT standard oneM2M platform is developed based on R2. In addition, it selects the specifications for e-IoT gateway devices that can sufficiently implement KEPCO's e-IoT standards. In addition, a technology and system for developing a high-performance gateway device that considers future scalability were proposed.

• Journal of the Korea Society of Computer and Information
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• v.25 no.1
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• pp.87-92
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• 2020

Various devices, which are powerful computer and low-performance sensors, is connected to IoT network. Accordingly, applying mutual authentication for devices and data encryption method are essential since illegal attacks are existing on the network. But cryptographic methods such as symmetric key and public key algorithms, hash function are not appropriate to low-performance devices. Therefore, this paper proposes blockchain-based lightweight IoT mutual authentication protocol for the low-performance devices.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.93-95
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• 2021

최근, 다양한 정보의 수집 및 처리가 필요한 스마트 홈, 의료, 교통, 제조 등 여러 산업 분야에서 IoT(Internet of Things)가 많이 활용되고 있다. 특히 스마트 홈 환경에서 IoT 장치로 수집되는 정보는 민감한 개인 정보를 포함할 수 있기 때문에 특정 그룹이나 개인만이 해당 정보에 접근할 수 있도록 관리할 필요가 있다. 또한, IoT 환경에서 Blockchain 기반으로 데이터의 신뢰성을 확보하는 분산 저장소의 경우, 지연 시간의 증가 문제가 발생될 수 있기 때문에 실시간 데이터 수집에 대한 처리 속도를 향상할 방안이 필요하다. 본 논문에서는 사용자와 IoT 장치 간 생성한 그룹 ID 로 해당 그룹에 대한 접근 권한을 관리하고, Hyperledger Fabric 과 별도의 데이터베이스 운용으로 실시간성, 신뢰성을 향상할 수 있는 Hyperledger Fabric 기반 스마트 홈 Architecture 를 제안한다. 이 Architecture는 IoT 장치가 사용되는 다양한 환경에서 보안성, 실시간성, 신뢰성을 향상할 수 있을 것이다.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.325-331
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• 2022

As IoT devices are used in various ways in an edge network environment, multiple studies are being conducted that utilizes the information collected from IoT devices in various applications. However, it is not easy to apply accurate IoT data immediately as IoT data collected according to network environment (interference, interference, etc.) are frequently missed or error occurs. In order to minimize mistakes in IoT data collected in an edge network environment, this paper proposes a management technique that ensures the reliability of IoT data by randomly generating signature values of IoT data and allocating only Security Information (SI) values to IoT data in bit form. The proposed technique binds IoT data into a blockchain by applying multiple hash chains to asymmetrically link and process data collected from IoT devices. In this case, the blockchainized IoT data uses a probability function to which a weight is applied according to a correlation index based on deep learning. In addition, the proposed technique can expand and operate grouped IoT data into an n-layer structure to lower the integrity and processing cost of IoT data.