• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.258-264
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• 2022

The smart farm for livestock, in which information and communication technology (ICT) is combined with livestock farm, is mostly based on the cloud computing paradigm. A cloud-based smart livestock farm has disadvantages such as increased response time, burden on cloud resource caused by the increased number of IoT sensors, traffic burden on the network, and lack of failure resilience mechanisms through collaboration with adjacent IoT devices. In this paper, with these problems in mind, we propose an IoT collaboration system based on edge computing. By using the relatively limited computing resources of the edge device to share the cloud's web server function, we aim to reduce the cloud's resources needed and improve response time to user requests. In addition, through the heartbeat-based failure recovery mechanism, IoT device failures were detected and appropriate measures were taken.

• Journal of the Korea Convergence Society
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• v.9 no.4
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• pp.57-63
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• 2018

IoT devices are used in many areas to perform various roles and functions in a cloud environment. However, a method of access control that can stably control the IoT device has not been proposed yet. In this paper, we propose a hierarchical multi-level property access control scheme that can perform stable access of IoT devices used in a cluster environment. In order to facilitate the access of the IoT device, the proposed method not only provides the ID key (security token) unique to the IoT device by providing the IoT Hub, but also allows the IoT Hub to authenticate the X.509 certificate and the private key, So that the private key of the IoT device can not be seen outside the IoT device. As a result of the performance evaluation, the proposed method improved the authentication accuracy by 10.5% on average and the processing time by 14.3%. The overhead of IoT Hub according to the number of IoT attributes was 9.1% lower than the conventional method.

• 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 Digital Convergence
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• v.18 no.10
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• pp.233-238
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• 2020

In the cloud environment, IoT devices using sensors and wearable devices are being applied in various environments, and technologies that accurately determine the information generated by IoT devices are being actively studied. However, due to limitations in the IoT environment such as power and security, information generated by IoT devices is very weak, so financial damage and human casualties are increasing. To accurately collect and analyze IoT information, this paper proposes a topographic information-based key management technique that considers IoT information errors. The proposed technique allows IoT layout errors and groups topographic information into groups of dogs in order to secure connectivity of IoT devices in the event of arbitrary deployment of IoT devices in the cloud environment. In particular, each grouped terrain information is assigned random selected keys from the entire key pool, and the key of the terrain information contained in the IoT information and the probability-high key values are secured with the connectivity of the IoT device. In particular, the proposed technique can reduce information errors about IoT devices because the key of IoT terrain information is extracted by seed using probabilistic deep learning.

• International Journal of Advanced Culture Technology
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• v.5 no.2
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• pp.90-97
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• 2017

The Internet of Things(IoT) market is expected to grow from 15.5billion to 75.4 billion by 2015-2025. As the number of IoT devices increases, the amount of data that is sent to the cloud is increasing. Today's Cloud Computing models are not suited to handle the vast amount of data generated by IoT devices. In this paper, we propose a Cooperation Coordinator System that reduces server load and improved real-time processing capability under specific circumstances by using Band-Cloud. The cooperation coordinator system dynamically forms the cloud when cooperation is needed between mobile devices located near. It is called Band-Cloud. Band-Cloud provides services entrusted by Central Cloud. This paper describes the proposed system and shows the cooperation process using the Android-based mobile devices and Wi-Fi Direct technology. Such a system can be applied to cases where real-time processing is required in a narrow area such as a hospital ward or a school classroom.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.227-229
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• 2015

모든 사물에 인터넷이 연결되는 사물 인터넷(IoT: Internet of Things)시대가 열렸다. IoT 디바이스들을 연결하기 위해 클라우드 또한 더욱 관심이 높아지고 있다. IoT 디바이스를 연결한 클라우드는 작은 단위의 작업들을 다량으로 수행하게 된다. IoT 서비스에서 발생하는 작업들을 효율적으로 처리하기 위해서는 적합한 작업 스케줄링이 반드시 필요하다. 본 논문에서는 오픈소스 기반의 플랫폼인 오픈스택(OpenStack)에서 Filter 스케줄러와 Chance 스케줄러를 VM 개수에 따라 단위 시간동안 성능을 비교 분석한다. 이를 통해 오픈스택에서 IoT 서비스 사용자들을 위해 합리적인 스케줄러 방법을 도출해낼 수 있다

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.31-42
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• 2023

As computer performance is leveled upward, the use of IoT systems is gradually expanding. Although IoT systems are used in many fields, it is true that it is difficult to build a safe system due to performance limitations. To overcome these limitations, many researchers have proposed numerous protocols to improve security issues. Among them, Azrour et al. except. We proposed a new efficient and secure authentication protocol for remote healthcare systems in a cloud-based IoT environment, and claimed that the new protocol could solve the security vulnerabilities of the existing protocols and was more efficient. However, in this paper, through the security analysis of the remote healthcare system in the cloud-based IoT environment proposed by Azrour et al., the protocol of this system was found to be vulnerable to Masquerade attack, Lack of Perfect Forward Secrecy, Off-line password guessing attack, and Replay attack.

• Journal of Convergence for Information Technology
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• v.9 no.4
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• pp.1-7
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• 2019

The medical environment, combined with IT technology, is changing the paradigm for medical services from treatment to prevention. In particular, as ICT convergence digital healthcare technology is applied to hospital medical systems, infrastructure technologies such as big data, Internet of Things, and artificial intelligence are being used in conjunction with the cloud. In particular, as medical services are used with IT devices, the quality of medical services is increasingly improving to make them easier for users to access. Medical institutions seeking to incorporate IoT services into cloud health care environment services are trying to reduce hospital operating costs and improve service quality, but have not yet been fully supported. In this paper, a patient information collection model from hospital IoT system, which has established a cloud environment, is proposed. The proposed model prevents third parties from illegally eavesdropping and interfering with patients' biometric information through IoT devices attached to the patient's body at hospitals in cloud environments that have established hospital IoT systems. The proposed model allows clinicians to analyze patients' disease information so that they can collect and treat diseases associated with their eating habits through IoT devices. The analyzed disease information minimizes hospital work to facilitate the handling of prescriptions and care according to the patient's degree of illness.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1147-1161
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• 2023

The Internet of Things (IoT) requires a new processing model that will allow scalability in cloud computing while reducing time delay caused by data transmission within a network. Such a model can be achieved by using resources that are closer to the user, i.e., by relying on edge computing (EC). The amount of IoT data also grows with an increase in the number of IoT devices. However, building such a flexible model within a heterogeneous environment is difficult in terms of resources. Moreover, the increasing demand for IoT services necessitates shortening time delay and response time by achieving effective load balancing. IoT devices are expected to generate huge amounts of data within a short amount of time. They will be dynamically deployed, and IoT services will be provided to EC devices or cloud servers to minimize resource costs while meeting the latency and quality of service (QoS) constraints of IoT applications when IoT devices are at the endpoint. EC is an emerging solution to the data processing problem in IoT. In this study, we improve the load balancing process and distribute resources fairly to tasks, which, in turn, will improve QoS in cloud and reduce processing time, and consequently, response time.