• 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.17 no.1
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• pp.185-201
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• 2023

Grant-free random access (GFRA) can reduce the access delay and signaling cost, and satisfy the short transmission packet and strict delay constraints requirement in internet of things (IoT). IoT is a major trend in the future, which is characterized by the variety of applications and devices. However, most existing studies on GFRA only consider a single type of device and omit the effect of access delay. In this paper, we study GFRA in multicell massive multipleinput multiple-output (MIMO) systems where different types of devices with various configurations and requirements co-exist. By introducing the backoff mechanism, each device is randomly activated according to the backoff parameter, and active devices randomly select an orthogonal pilot sequence from a predefined pilot pool. An analytical approximation of the average spectral efficiency for each type of device is derived. Based on it, we obtain the optimal backoff parameter for each type of devices under their delay constraints. It is found that the optimal backoff parameters are closely related to the device number and delay constraint. In general, devices that have larger quantity should have more backoff time before they are allowed to access. However, as the delay constraint become stricter, the required backoff time reduces gradually, and the device with larger quantity may have less backoff time than that with smaller quantity when its delay constraint is extremely strict. When the pilot length is short, the effect of delay constraints mentioned above works more obviously.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3068-3078
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• 2015

Although the massive MIMO system supports a high throughput, it requires a lot of channel information for channel compensation. For the reduction of overhead, the massive MIMO system generally uses TDD as duplexing scheme. Therefore, the massive MIMO system is sensitive to rapidly changing fast fading in according to time. For the improvement of reduced SINR by fast fading, the adaptive power control is proposed. Unlike the conventional scheme, the proposed scheme considers mobility of device for adaptive power control. The simulation of the proposed scheme is performed with consideration for mobility of device. The result of the simulation shows that the proposed scheme improves SINR. Since SINR is decreased in according to the number of device in the network by unit of cell, each base station can accommodate more devices by the proposed scheme. Also, because the massive MIMO system with high SINR can use high order modulation scheme, it can support higher throughput.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.974-987
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• 2018

This paper presents a novel and efficient data transmission scheme based on mobile edge computing for the massive IoT environments which should support various type of services and devices. Based on an accurate and precise synchronization process, it maximizes data transmission throughput, and consistently maintains a flow's latency. To this end, the proposed efficient software defined data transmission scheme (ESD-DTS) configures and utilizes synchronization zones in accordance with the 4 usage cases, which are end node-to-end node (EN-EN), end node-to-cloud network (EN-CN), end node-to-Internet node (EN-IN), and edge node-to-core node (EdN-CN); and it transmit the data by the required service attributes, which are divided into 3 groups (low-end group, medium-end group, and high-end group). In addition, the ESD-DTS provides a specific data transmission method, which is operated by a buffer threshold value, for the low-end group, and it effectively accommodates massive IT devices. By doing this, the proposed scheme not only supports a high, medium, and low quality of service, but also is complied with various 5G usage scenarios. The essential difference between the previous and the proposed scheme is that the existing schemes are used to handle each packet only to provide high quality and bandwidth, whereas the proposed scheme introduces synchronization zones for various type of services to manage the efficiency of each service flow. Performance evaluations show that the proposed scheme outperforms the previous schemes in terms of throughput, control message overhead, and latency. Therefore, the proposed ESD-DTS is very suitable for upcoming 5G networks in a variety of massive IoT environments with supporting mobile edge computing (MEC).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.43-48
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• 2021

One of the effective ways to increase data transmission rate is to use massive antenna technique where tens or hundreds of antennas are deployed in base station and spatial diversity gain is improved by multiuser method. If multiuser method is applied, there will be inter-user interference and maximal ratio combiner (MRC) is conventionally used to reduce the complexity of the receiver and to eliminate interference. However, as the number of mobile devices increases, the performance of the conventional receiver becomes deteriorated. To solve this problem, we propose a new detector that completely eliminates the interference from the registered devices and reduces that from the unregistered devices. Then, to reduce the complexity of the proposed scheme, we propose adaptive algorithm of the proposed scheme. Through simulation, we show that the proposed scheme has better bit error rate performance than the conventional scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.742-756
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• 2022

A flood of information has occurred with the rise of the internet and digital devices in the fourth industrial revolution era. Every millisecond, massive amounts of structured and unstructured data are generated; smartphones, wearable devices, sensors, and self-driving cars are just a few examples of devices that currently generate massive amounts of data in our daily. Machine learning has been considered an approach to support and recognize patterns in data in many areas to provide a convenient way to other sectors, including the healthcare sector, government sector, banks, military sector, and more. However, the conventional machine learning model requires the data owner to upload their information to train the model in one central location to perform the model training. This classical model has caused data owners to worry about the risks of transferring private information because traditional machine learning is required to push their data to the cloud to process the model training. Furthermore, the training of machine learning and deep learning models requires massive computing resources. Thus, many researchers have jumped to a new model known as "Federated Learning". Federated learning is emerging to train Artificial Intelligence models over distributed clients, and it provides secure privacy information to the data owner. Hence, this paper implements Federated Averaging with a Deep Neural Network to classify the handwriting image and protect the sensitive data. Moreover, we compare the centralized machine learning model with federated averaging. The result shows the centralized machine learning model outperforms federated learning in terms of accuracy, but this classical model produces another risk, like privacy concern, due to the data being stored in the data center. The MNIST dataset was used in this experiment.

• Electronics and Telecommunications Trends
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• v.37 no.1
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• pp.32-41
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• 2022

With the development of computing technology, the convergence of ICT with existing traditional industries is being attempted. In particular, with the recent advent of 5G, connectivity with numerous AuT (autonomous Things) in the real world as well as simple mobile terminals has increased. As more devices are deployed in the real world, the need for technology for devices to learn and act autonomously to communicate with humans has begun to emerge. This article introduces "Device to the Edge," a new computing paradigm that enables various devices in smart spaces (e.g., factories, metaverse, shipyards, and city centers) to perform ultra-reliable, low-latency and high-speed processing regardless of the limitations of capability and performance. The proposed technology, referred to as EdgeCPS, can link devices to augmented virtual resources of edge servers to support complex artificial intelligence tasks and ultra-proximity services from low-specification/low-resource devices to high-performance devices.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1349-1355
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• 2016

It should guarantee high reliability and ultra low latency communication. Additionally, it should support connection between massive devices. As one of estimated scenarios for 5G mobile communication, mobile devices and sensors using low data rate wireless communication will increase. For communication of these devices, single-carrier system can be considered. In order to satisfy these requirements, in this paper, we propose CDMA (Code Division Multiple Access) system using complex spreading and Multi-level BPSK(Binary Phase Shift Keying). The proposed system spread transmit symbol by using chip code consisted of real and imaginary number. As simulation results, we can confirm that although the proposed system has 3dB lower BER (Bit Error Rate) performance than conventional CDMA system, the proposed system can support 2 times more users in comparison with conventional CDMA system.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.10a
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• pp.64-67
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• 2003

The authors have settled general modular design by analyzing related literatures, but general modular design are too massive to be applicable to all process devices. So, the common parts have to be selected, applied, and modified for the devices. We have chosen the dry pulverizing/mixing device for example. We have elected the target modules of this device such as flange, hinge, bolt, nut coupling. The remote assembling and disassembling possibilities of the selected modules have been analyzed from the viewpoints of visibility, interference, approach, weight and so on. We have presented final modular design proper to the target modules. The modular designs which have adopted the modular property been analyzed. The modular design points are comprised of common and unique points. Some points are common for several devices, such as bolt, flange and so on. Others are unique for each device, such as power transmission coupling. The experimental devices have been modified by these modular design points and the design drawings have been presented.

• Journal of Digital Contents Society
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• v.15 no.4
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• pp.527-532
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• 2014

Recently, due to the proliferation of mobile smart devices, the inovation of bigdata, which analyzes and processes massive data collected from various sensors implaned in smart devices, expands to LBSs. Many location prediction techniques for moving objects have been studied in literature. However, as the majority of studies perform location prediction which depends on specific applications, they hardly reflect the technical requirements of next-generation spatio-temporal information services. Therefore, this paper proposes the design of general-purpose distributed moving object prediction query processing framework that is capable of performing primitive and various types of queries effectively based on massive spatio-temporal data of moving objects in real-world space networks.