• Journal of KIISE
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• v.43 no.7
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• pp.786-794
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• 2016

Recommender systems can be used to assist users in selecting required services for their tasks in Internet of Things (IoT) environments in which diverse services can be provided by utilizing IoT devices. Traditional research on recommendation mainly focuses on predicting preferences of individual users. However, in IoT environments, not only individual users but also groups of users can access services in the environments. In this study, we analyzed user groups' preferences on services and developed service recommendation approach for new groups that do not have a history of accessing IoT-services in a certain place. Our approach extends the traditional user-based collaborative filtering by considering the similarity between user groups based on their member organization. We conducted experiments with a real-world dataset collected from IoT testbed environments. The results demonstrate that the proposed approach is effective to recommend services to new user groups in IoT environments.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.197-202
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• 2022

IoT (Internet of Things) devices are being attacked by malware due to many security vulnerabilities, such as the use of weak IDs/passwords and unauthenticated firmware updates. However, due to the diversity of CPU architectures, it is difficult to set up a malware analysis environment and design features. In this paper, we design time series features using the byte sequence of executable files to represent independent features of CPU architectures, and analyze them using recurrent neural networks. The proposed feature is a fixed-length time series pattern extracted from the byte sequence by calculating partial entropy and applying linear interpolation. Temporary changes in the extracted feature are analyzed by RNN and LSTM. In the experiment, the IoT malware detection showed high performance, while low performance was analyzed in the malware family classification. When the entropy patterns for each malware family were compared visually, the Tsunami and Gafgyt families showed similar patterns, resulting in low performance. LSTM is more suitable than RNN for learning temporal changes in the proposed malware features.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.440-448
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• 2019

The Internet of Things (IoT) is one of the main enablers for situation awareness needed in accomplishing smart cities. IoT devices, especially for monitoring purposes, have stringent timing requirements which may not be met by cloud computing. This deficiency of cloud computing can be overcome by fog computing for which fog nodes are placed close to IoT devices. Because of low capabilities of fog nodes compared to cloud data centers, fog nodes may not be deployed with all the services required by IoT devices. Thus, in this article, we focus on the issue of fog service placement and present the recent research trends in this issue. Most of the literature on fog service placement deals with determining an appropriate fog node satisfying the various requirements like delay from the perspective of one or more service requests. In this article, we aim to effectively place fog services in accordance with the pre-obtained service demands, which may have been collected during the prior time interval, instead of on-demand service placement for one or more service requests. The concept of the logical fog network is newly presented for the sake of the scalability of fog service placement in a large-scale smart city. The logical fog network is formed in a tree topology rooted at the cloud data center. Based on the logical fog network, a service placement approach is proposed so that services can be placed on fog nodes in a resource-effective way.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.641-643
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• 2021

The Internet of Things (IoT) connects all markets and industries, enabling new business models for a variety of services and service providers. The Internet of Medical Things (IoMT) not only accelerates medical advances, but also enables treatment with a more human approach. In addition, it improves treatment methods and quality of precision medical care through data, enables timely treatment, and improves operational productivity of medical institutions through a simplified workflow. However, since the medical field directly affects human health and life, securing security has become an issue above all else, and is a target for hackers trying to exploit it. Therefore, in this study, IoMT technology and security threats and countermeasures in the medical field are analyzed.

• Annual Conference of KIPS
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• 2018.05a
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• pp.604-607
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• 2018

From the last past decade, the Internet of Thing (IoT) area has attracted a lot of attention from researchers. It is said to be a promising technology with great impact in people life, since it redefines the relationship objects have with Human and between themselves. It allows objects to gather data from the real world and communicate with others through the internet. This enabled many opportunities for service providers, companies, factories, environmental monitoring, healthcare, smart cities, and soon. Therefore, today, IoT is densely used in various domains of life, and knows an exponential growth. However, although many advancements have been achieved, several challenges keep causing issues and still need to be overcome. This paper gives an overview on the current trend issues in IoT on which researchers are focusing. It's also explores different proposed frameworks to allow the application of cognitive computing as an integrated process of an Internet of things (IoT) systems, to bring a great advanced in the way machine may communicate with human and their surroundings. This is known as cognitive IoT (CIoT), which allows machines to produce a human-like behavior, then providing enhanced level of capabilities to IoT.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.01a
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• pp.59-62
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• 2016

최근 무선통신기술과 소형 하드웨어의 발전으로 모든 환경에서 네트워크 및 컴퓨팅이 가능한 IoT(Internet of Things) 기기들이 지속적으로 증가하는 추세이며, 이러한 IoT 트랜드는 지속될 전망이다. 기존 IoT 플랫폼은 일반적으로 전력 사용적인 측면에서 In-memory 컴퓨팅을 지향하지만 이러한 방식은 시스템 에러 발생 시 메모리의 휘발성으로 인해 신뢰성이 저하되는 단점이 있다. 본 논문에서는 전체 시스템의 신뢰성 향상을 위해 XML 형식의 파일과 관계형 데이터베이스를 이용한 IoT 기반 상황 인식 시스템 서버를 설계한다. 설계된 상황 인식 시스템 서버는 추론 엔진을 포함하고 있으며, 사용자가 등록한 룰과 수집된 상황 데이터를 이용하여 전체 시스템을 동작시킨다. 또한, 전체 시스템의 신뢰성을 검증하기 위해 3가지 동작 시나리오를 제안한다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.778-783
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• 2018

With the rapid advancement of information and communication technology and industrial technologies, a hyper-connected society is being realized to connect human beings, all programs and things via the Internet. IoT (Internet of Thing), which connects a thing and another thing, and things and human beings, gathers information to realize the hyper-connected society. MQTT (Message Queuing Telemetry Transport) is a push-technology-based light message transmission protocol that was developed to be optimized to the limited communication environment such as IoT. In pursuing the hyper-connected society, IoT's sensor environment information is now being used as a wide range of information on people's diseases and health management. Thus, security problems of such MQTT include not only the leak of environmental information but also the personal information infringement. To resolve such MQTT security problems, we have designed a new security MQTT communication by applying the initial-value sensitivity and pseudorandomness of the chaotic system to the integrity and confidentiality. The encryption method using our proposed chaotic system offers a simple structure and a small amount of calculation, and it is deemed to be suitable to the limited communication environment such as IoT.

• Journal of Korea Multimedia Society
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• v.20 no.9
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• pp.1559-1566
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• 2017

Recently in the IoT(Internet of Things) environment, a data collection in real-time through device's sensor has increased with an emergence of various devices. Collected data from IoT environment shows a large scale, non-uniform generation cycle and atypical. For this reason, the distributed processing technique is required to analyze the IoT sensor data. However if you do not consider the optimal scheduling for data and the processor of IoT in a distributed processing environment complexity increase the amount in assigning a task, the user is difficult to guarantee the QoS(Quality of Service) for the sensor data. In this paper, we propose APQTA(Adaptive Priority Queue-driven Task Allocation method for sensor data processing) to efficiently process the sensor data generated by the IoT environment. APQTA is to separate the data into job and by applying the priority allocation scheduling based on the deadline to ensure that guarantee the QoS at the same time increasing the efficiency of the data processing.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.301-311
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• 2021

The technological advancements of the last two decades directed the era of the Internet of Things (IoT). IoT enables billions of devices to connect through the internet and share their information and resources on a global level. These devices can be anything, from smartphones to embedded sensors. The main purpose of IoT is to make devices capable of achieving the desired goal with minimal to no human intervention. Although it hascome as a social and economic blessing, it still brought forward many security risks. This paper focuses on providing a survey of the most commonly used application layer protocols in the IoT domain, namely, Constrained Application Protocol (CoAP), Message Queuing Telemetry Transport (MQTT), Advanced Message Queuing Protocol (AMQP), and Extensible Messaging and Presence Protocol (XMPP). MQTT, AMQP, and XMPP use TCP for device-to-device communication, while CoAP utilizes UDP to achieve this purpose. MQTT and AMQP are based on a publish/subscribe model, CoAP uses the request/reply model for its structuring. In addition to this, the quality of service provision of MQTT, AMQP, and CoAP is not very high, especially when the deliverance of messages is concerned. The selection of protocols for each application is very a tedious task.This survey discusses the architectures, advantages, disadvantages, and applications of each of these protocols. The main contribution of this work is to describe each of the aforementioned application protocols in detail as well as providing their thorough comparative analysis. This survey will be helpful to the developers in selecting the protocol ideal for their system and/or application.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.887-888
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• 2016

Internet data for IoT(Internet of Things) period was changed in such a way that the data is done by sharing information for the user. However, in the existing system IoT environment for the user to utilize the system it has a problem does not take into account the individual characteristics. And there must be an intermediate vectors are capable of controlling problems such as Dongle. In this paper, through the flow sensor control applications as a way to solve this problem to control the flow of the sensor according to the characteristics desired by the user. Due to this makes it possible to easily manage the sensor compared to conventional IoT environment. Accordingly, the user must manage the sensor through the application regardless of time and place. So it is believed to reduce the unnecessary power consumption is possible effective control sensor.