• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.535-538
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• 2022

For Plug & Play of IoT devices, we develop a module that recognizes the type of USB, which is a typical wired interface of IoT devices, through image recognition. In order to drive an IoT device, a driver for communication and device hardware is required. The wired interface for connecting to the IoT device is recognized by using the image obtained through the camera of smartphone shooting to recognize the corresponding communication interface. For USB, which is a most popular wired interface, types of USB are classified through artificial neural network-based machine learning. In order to secure sufficient data set of artificial neural networks, USB images are collected through the Internet, and additional image data sets are secured through image processing. In addition to the convolution neural networks, recognizers are implemented with various deep artificial neural networks, and their performance is compared and evaluated.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.196-201
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• 2018

Recently, various infrastructure-less IoT networking schemes have been studied to construct local IoT networks based on self-organization. This is, because RPL protocol, which is to support infrastructure based network construction is used to construct local IoT networks. Thus, a self-organization networking and ad hoc path between client and server in local IoT networks is not supported in basis RPL protocol. In this paper, we propose a self-organization networking scheme which support infrastructure-less based IoT network construction in low-power and lossy network based IoT environments consisting of IoT devices with the constrained feature, such as low power, the limited transmission rate and low computing capacity. Through simulation, we show that the proposed self-organization networking scheme improves the performance, in terms of the number of packets generated for end-to end data transmission and the end-to-end delay, compared to basis RPL protocol.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.2
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• pp.269-276
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• 2016

Internet of Things (IoT) is based on wireless networks being able to connect things and people on a large scale. In the IoT environment, reliable broadcast plays an important role to distribute data to a large number of devices. Energy harvesting from a surrounding environment is a key technique to achieve a sustainable IoT network. In IoT networks, a problem of transmission errors and energy shortage should be mitigated for reliable broadcast. In this paper, we propose an energy-efficient and reliable broadcast method to consider packet errors and energy consumption in the environment where a large number of nodes are connected. The proposed scheme can improve data restoration probability by up to 15% and reduce energy consumption by up to 17%.

• Journal of Industrial Convergence
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• v.20 no.6
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• pp.37-45
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• 2022

With the development of the Internet of Things (IoT), related network infrastructures require new technologies to protect against threats such as external hacking. This study proposes an L-PBFT consensus algorithm that can protect IoT networks based on a blockchain consensus algorithm. We designed a blockchain (private) model suitable for small networks, tested processing performance for ultra-small/low-power IoT devices, and verified stability. As a result of performance analysis, L-PBFT proved that at least the number of nodes complies with the operation of the consensus algorithm(minimum 14%, maximum 29%) and establishes a trust network(separation of secure channels) different from existing security protocols. This study is a 4th industry convergence research and will be a foundation technology that will help develop IoT device security products in the future.

• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.33-39
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• 2020

Interest in 5G communication security has been growing recently amid growing expectations for 5G technology with faster speed and stability than LTE. However, 5G has so far included disparate areas, so it has not yet fully supported the issues of security. This paper proposes a blockchain-based IoT management model in order to efficiently provide the authentication of users using IoT in 5G In order to efficiently fuse the authentication of IoT users with probabilistic theory and physical structure, the proposed model uses two random keys in reverse direction at different layers so that two-way authentication is achieved by the managers of layers and layers. The proposed model applied blockchain between grouped IoT devices by assigning weights to layer information of IoT information after certification of IoT users in 5G environment is stratified on a probabilistic basis. In particular, the proposed model has better functions than the existing blockchain because it divides the IoT network into layered, multi-layered networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.946-959
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• 2018

Recently interest in Internet of Things(IoT) has attracted significant attention at national level. IoT can create new services as a technology to exchange data through connections among a huge number of objects around the user. Data communication between objects provides not only information collected in the surrounding environment but also various personalized information. IoT services which provide these various types of data are exposed to numerous security vulnerabilities. If data is maliciously collected and used by an attacker in an IoT environment that deals with various data, security threats are greater than those in existing network environments. Therefore, security of all data exchanged in the IoT environment is essential. However, lightweight terminal devices used in the IoT environment are not suitable for applying the existing encryption algorithm. In addition, IoT networks consisting of many sensors require group communication. Therefore, this paper proposes a secure multicast scheme using the proxy re-encryption method based on Vehicular ad-hoc networks(VANET) environment. The proposed method is suitable for a large-scale dynamic IoT network environment using unreliable servers.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.267-280
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• 2023

With development of computing and communications technologies, IoT environments based on high-speed networks have been extending rapidly. Especially, from home to an office or a factory, applications of IoT devices with sensing environment and performing computations are increasing. Unfortunately, IoT devices which have limited hardware resources can be vulnerable to cyber attacks. Hence, there is a concern that an IoT botnet can give rise to information leakage as a national cyber security crisis arising from abuse as a malicious waypoint or propagation through connected networks. In order to response in advance from unknown cyber threats in IoT networks, in this paper, We firstly define four types of We firstly define four types of characteristics by analyzing darknet traffic accessed from an IoT botnet. Using the characteristic, a suspicious IP address is filtered quickly. Secondly, the filtered address is identified by Cyber Threat Intelligence (CTI) or Open Source INTelligence (OSINT) in terms of an unknown suspicious host. The identified IP address is finally fingerprinted to determine whether the IP is a malicious host or not. To verify a validation of the proposed method, we apply to a Darknet on real-world SOC. As a result, about 1,000 hosts who are detected and blocked preemptively by the proposed method are confirmed as real IoT botnets.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.1-12
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• 2022

Besides unexpected growth perceived by IoT's, the variety and volume of threats have increased tremendously, making it a necessity to introduce intrusion detections systems for prevention and detection of such threats. But Intrusion Detection and Prevention System (IDPS) inside the IoT network yet introduces some unique challenges due to their unique characteristics, such as privacy inference, performance, and detection rate and their frequency in the dynamic networks. Our research is focused on the privacy inferences of existing intrusion prevention and detection system approaches. We also tackle the problem of providing unified a solution to implement the open-source IDPS in the IoT architecture for assessing the performance of IDS by calculating; usage consumption and detection rate. The proposed scheme is considered to help implement the human health monitoring system in IoT networks

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.743-749
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• 2020

Internet of Things (IoT) is a growing technology along with artificial intelligence (AI) technology. Recently, increasing cases of developing knowledge services using information collected from sensor data have been reported. Communication is required to connect the IoT and AI, and 5G mobile networks have been widely spread recently. IoT, AI services, and 5G mobile networks can be configured and used as sensor-mobile edge-server. The sensor does not send data directly to the server. Instead, the sensor sends data to the mobile edge for quick processing. Subsequently, mobile edge enables the immediate processing of data based on AI technology or by sending data to the server for processing. 5G mobile network technology is used for this data transmission. Therefore, this study examines the challenges, opportunities, and solutions used in each type of technology. To this end, this study addresses clustering, Hyperledger Fabric, data, security, machine vision, convolutional neural network, IoT technology, and resource management of 5G mobile networks.

• 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.