• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.2
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• pp.337-344
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• 2017

The ICT industry is changing. From the PC to mobile devices, and from the mobile devices to wearable and IoT devices, it is changing. It requires the OS for the IoT, coming out various IoT OS have been developed in accordance with this need. In this paper, we discuss the kind of OS that supports IoT device, analyze the technology trends.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.10-14
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• 2019

The number of security incidents is increasing as the Internet of Things(IoT) is distributed widely. The security incidents of IoT can cause financial damages. Moreover, It can become direct threats to humans. In order to prevent these problems, the security installation for IoT devices is important. This paper describes the definition of IoT devices, security incident case, architecture, and the security threats that can occur when a device is connected to network without security installation.

• Convergence Security Journal
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• v.18 no.2
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• pp.49-58
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• 2018

As the demand for Internet of Things(IoT) increases, the need for the security of IoT devices is increasing steadily. It is difficult to apply the conventional security theory to IoT devices because IoT devices are subject to be constrained by some factors such as hardware, processor, and energy. Nowadays we have several security guidelines and related documents on IoT device. Most of them, however, do not consider the characteristics of specific IoT devices. Since they describes the security issues comprehensively, it is not easy to explain the specific security level reflecting each characteristics of IoT devices. In addition, most existing guidelines and related documents are described in view of developers and service proposers, and thus ordinary users are not able to assess whether a specific IoT device can protect their information securely or not. We propose an security evaluation model, based on the existing guidelines and related documents, for more specific IoT devices and prove that this approach is more convenient to ordinary users by creating checklists for the smart watch.

• Journal of Internet of Things and Convergence
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• v.8 no.1
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• pp.79-85
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• 2022

Internet of Things (IoT) connects devices with various platforms, computing power, and functions. Due to the diversity of networks and the ubiquity of IoT devices, demands for security and privacy are increasing. Therefore, cryptographic mechanisms must be strong enough to meet these increased requirements, while at the same time effective enough to be implemented in devices with long-range specifications. In this paper, we present the performance and memory limitations of modern cryptographic primitives and schemes for different types of devices that can be used in IoT. In addition, detailed performance evaluation of the performance of the most commonly used encryption algorithms in low-spec devices frequently used in IoT networks is performed. To provide data protection, the binary ring uses encryption asymmetric fully homomorphic encryption and symmetric encryption AES 128-bit. As a result of the experiment, it can be seen that the IoT device had sufficient performance to implement a symmetric encryption, but the performance deteriorated in the asymmetric encryption implementation.

• Journal of Korea Multimedia Society
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• v.24 no.6
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• pp.789-795
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• 2021

In order to provide useful Internet of Things (IoT) services, the locations of IoT devices should be well managed. However, frequent location updates of lots of IoT devices result in signaling overhead in networks. To solve this problem, this paper utilizes the opportunistic fog node (OFN) which is opportunistically available according to the mobility to perform the location updates as a representative of IoT devices. Therefore, the location updates through OFN can reduce the signaling loads of networks. To show the performance of the proposed scheme, we develop an analytic model for the opportunistic location update offloading probability that the location update can be offloaded to OFN from the IoT device. Then, the extensive simulation results are given to validate the analytic model and to assess the performance of the proposed scheme in terms of the opportunistic location update offloading probability.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.6
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• pp.909-917
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• 2018

Recently, the Internet of Thing (IoT) technology is expanding explosively in the number of devices and applications in many application areas. In IoT systems, sensors and actuators are connected to the Internet and cooperate to do some applications by exchanging information. In this paper an IoT smart home system is developed to monitor and control home devices easily. Our system consists of sensor devices, IoT gateways, and an IoT server. Sensor devices developed using Rfduino sense the physical world and transmit their data using BLE to the IoT server thru the IoT gateway. We implemented the IoT gateway using Raspberry Pi and the IoT server using ARTIK cloud. We installed our system and made a test in our lab, which showed that our system can be installed and managed easily and extended its functionality in an easy way. By taking advantage of the rule mechanism and action messages of ARTIK cloud, we implemented the control of device parameters easily by sending action messages to the ARTIK cloud.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.2
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• pp.343-351
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• 2017

With ICT technology develops, IoT environment is attracting attention. However, IoT devices have various CPU performance as much as various purpose of use. Some IoT devices use the cpu that doesn't support public key cryptogrphy or crypto acceleration. In this paper, we study Blockchain-based IoT Device Authentication Scheme that provides authentication, integirity and non-repudation through analysis of Lamport Hash-chain, Lamport Signature, Blockchain and existing Authentication protocols. The proposed scheme requires only simple hash operation in IoT devices and it can operate in low performance IoT device, thus ensuring secure authentication in IoT environment.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.10
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• pp.337-350
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• 2014

Internet-of-Things(IoT) is the computing paradigm converged with different technologies, where diverse devices are connected via the wireless network, acquire environmental information from their equipped sensors, and are actuated. IoT applications provide smart services to users by interacting with multiple devices connected to the network. IoT devices provide the simple set of the information and also offer smart services by collaborating with other devices. That is, IoT applications always interact with IoT devices which are becoming very popular at a fast pace. However, due to this fact, developing IoT application results in unconventional technical challenges which have not been observed in typical software applications. Moreover, since IoT computing has its own characteristics which are distinguished from other former paradigms such as embedded computing and mobile computing, IoT applications also reveal their own technical challenges. Therefore, we analyze technical challenges occurring in developing IoT applications and present effective solutions to overcome the challenges. To verify identified issues and presented solutions, we present the result of performing a case study of developing an IoT application. Through the case study, we verify how the unconventional technical issues are raised in a real domain and analyze effectiveness of applying the solutions to the application.

• Electronics and Telecommunications Trends
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• v.35 no.1
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• pp.49-59
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• 2020

This paper describes an IoT-based electrical safety management system for managing the electrical power distribution systems in factories or buildings and for managing private electrical devices in apartment complex. The IoT-based electrical safety management system collects IoT data from the electrical facilities or devices to provide various electrical safety services. In some cases, it uses an IoT adaptor to collect data from legacy facilities. By monitoring and analyzing the IoT data, it is possible to provide protection from and prevent electrical hazards. In addition, an IoT-based electrical safety management system can benefit from using the IoT identification system and standardized data model of the electrical facilities and devices. An IoT identification system is used to increase manageability of large-scale electrical facilities which consists of numerous IoT devices. A standardized data model is used to support interoperability. This paper also explores some international and Korean standards related to IoT-based electrical safety management.