• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.984-987
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• 2018

In an Internet of Thing (IoT) environment, entities with different attributes and capacities are going to be connected in a highly connected fashion. Specifically, not only the mechanical and electronic devices but also other entities such as people, locations and applications are connected to each other. Understanding and managing these connections play an important role for businesses, which identify opportunities for new IoT services. Traditional approach for storing and querying IoT data is used of a relational database management system (RDMS) such as MySQL or MSSQL. However, using RDMS is not flexible and sufficient for handling heterogeneous IoT data because these data have deeply complex relationships which require nested queries and complex joins on multiple tables. In this paper, we propose a graph model for constructing a graph database of heterogeneous IoT data. Graph databases are purposely-built to store highly connected data with nodes representing entities and edges representing the relationships between these entities. Our model fuses social graph, spatial graph, and things graph, and incorporates the relationships among them. We then present a case study which applies our model for representing data from a Smart Campus using Neo4J platform. Through the results of querying to answer real questions in Smart Campus management, we show the viability of our model.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.315-320
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• 2021

While blockchain platforms for various purposes have been developed and the blockchain ecosystem is being developed, interoperability problems are emerging in which each blockchain is isolated and operated. In this study, we introduce interchain and sidechain technologies, which are blockchain that connect blockchain, and explain examples of using heterogeneous blockchain transactions and functions by applying them. In addition, blockchain, artificial intelligence, and IoT technologies, which are drawing attention in the fourth industrial revolution, are going through a process of converging and developing beyond their own development. In this regard, we present processes for combining artificial intelligence or IoT in blockchain, and propose a model that can operate without intervention by applying the combination of blockchain and artificial intelligence IoT to processes for trading and exchange between heterogeneous blockchain.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.17-26
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• 2023

A smart city is a massive internet of things (IoT) environment, where all terminal devices are connected to a network to create and share information. In accordance with massive IoT environments, millions of IoT devices are connected, and countless data are generated in real time. However, since heterogeneous IoT devices are used, collecting the logs for each IoT device is difficult. Due to these issues, when an IoT device is invaded or is engaged in malicious behavior, such as infection with malware, it is difficult to respond quickly, and additional damage may occur due to information leakage or stopping the IoT device. To solve this problem, in this paper, we propose identifying the attack technique used for initial access to IoT devices through MITRE ATT&CK, collect the logs that can be generated from the identified attack technique, and use them to identify the cause of malware infection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3615-3638
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• 2020

Node identity authentication is an essential means to ensure the security of the Internet of Things. Existing blockchain-based IoT node authentication schemes have many problems. A heterogeneous IoT node authentication scheme based on an improved hybrid blockchain is proposed. Firstly, the hybrid blockchain model is designed to make the blockchain and IoT environment more compatible. Then the proxy node selection mechanism is intended to establish a bridge between the ordinary IoT node and the blockchain, building by calculating the trust value between nodes. Finally, based on the improved hybrid blockchain, the node authentication scheme of the model and proxy node selection mechanism establishes a secure connection for communication between nodes. Safety and performance analysis shows proper safety and performance.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.3
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• pp.81-90
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• 2018

Due to the dramatic advancement of IoT (Internet of Things), it is expected that tens of billions of IoT devices will be connected by the year 2024. Furthermore, as IoT technologies evolves, the security management in IoT platforms has become a critical issue. For example, there are interworking problems between heterogeneous IoT platforms caused by differences from communication protocols, security policies, etc. in each platform. In addition, unsecured interworking can cause major security issues including the information leakage. In this paper, in order to solve these problems, a security interworking architecture is proposed and implemented in both FIWARE and oneM2M, which are representative IoT platforms. First, the security architecture of FIWARE is analyzed and implemented, and then the security framework based on OAuth 2.0 is developed on Mobius platform. Finally, in order to validate the proposed security interworking architecture, a LED (Light-Emitting Diode) example, where the LED is controlled by only authorized users, is developed. The proposed architecture can be extended to the diverse IoT platforms and devices.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.1279-1282
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• 2017

현재 사물인터넷(Internet of Things; IoT) 기술을 이용한 스마트홈 환경을 구축하기 위해서는 같은 식별체계를 사용하는 플랫폼 디바이스를 사용해야 한다. 그러나 주요 IoT 플랫폼들은 각각 다른 식별체계를 사용하고 있기 때문에 이종 플랫폼 간 디바이스 식별이 어려운 상황이다. 이종 플랫폼 간 디바이스 식별체계 상호연동에 대한 연구는 진행 중이며 아직까지 해결책은 제시되지 않았다. 따라서 본 논문에서는 주요 IoT 플랫폼인 oneM2M, GS1 Oliot, IBM Watson IoT, OCF IoTivity의 디바이스 식별체계를 분석하고 비교하여 서로 다른 플랫폼 간 디바이스 식별체계에 대한 번역기 또는 해석기의 필요성과 개념모델을 제시한다.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.108-112
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• 2021

For smart mobile devices, the wireless communication module is one of the hardware modules that consume the most energy. If we can build a multi-channel multi-interface environment using heterogeneous communication modules and operate them dynamically, data transmission performance can be highly improved by increasing the parallelism. Also, because these heterogeneous modules have different data rates, transmission ranges, and power consumption, we can save energy by exploiting a power efficient and low speed wireless interface module to transmit/receive sporadic small data. In this paper, we propose a power efficient data transmission method using heterogeneous communication networks. We also compared the performance of our proposed scheme to a conventional scheme, and proved that our proposed scheme can save energy while guaranteeing reasonable data delivery time.

• Advanced Industrial SCIence
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• v.2 no.3
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• pp.8-14
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• 2023

The majority of IoT devices already employ AIoT, however there are still numerous issues that need to be resolved before AI applications can be deployed. In order to more effectively distribute IoT edge resources, this paper propose a machine learning-based approach to managing IoT edge resources. The suggested method constantly improves the allocation of IoT resources by identifying IoT edge resource trends using machine learning. IoT resources that have been optimized make use of machine learning convolution to reliably sustain IoT edge resources that are always changing. By storing each machine learning-based IoT edge resource as a hash value alongside the resource of the previous pattern, the suggested approach effectively verifies the resource as an attack pattern in a distributed AIoT context. Experimental results evaluate energy efficiency in three different test scenarios to verify the integrity of IoT Edge resources to see if they work well in complex environments with heterogeneous computational hardware.

• Journal of Software Assessment and Valuation
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• v.15 no.1
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• pp.123-131
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• 2019

The Internet of Things (IoT) environment must be able to meet the needs of users by providing access to various services that can be used to develop diverse user applications. However, QoS issues arise due to the characteristics of the IoT environment, such as numerous heterogeneous devices and potential resource constraints. In this paper, we propose a QoS prediction method that reflects trust between users in SOA based IoT. In order to increase the accuracy of QoS prediction, we analyze the trust and distrust relations between users and identify similarities among users and predict QoS based on them. The centrality is calculated to enhance trust relationships. Experimental results show that QoS prediction can be improved.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.1
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• pp.51-58
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• 2015

Internet of Thing is a collection of various technical components, and the interworking among heterogeneous devices, networks, applications is expected to be accelerated through the openness of IoT platform. For this reason, many technical and administrative security threats will occur in IoT environments. In this paper, authentication methods of recent researches are analyzed for safe IoT services, and new mutual authentication protocol is proposed to provide more secure communication. The proposed protocol prevents an impersonation as malicious gateway or illegal device providing mutual authentication between gateway and IoT device. The performance analysis and evaluation of proposed authentication protocol are performed.