• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.177-189
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• 2023

Malware detection is an increasingly important operational focus in cyber security, particularly given the fast pace of such threats (e.g., new malware variants introduced every day). There has been great interest in exploring the use of machine learning techniques in automating and enhancing the effectiveness of malware detection and analysis. In this paper, we present a deep recurrent neural network solution as a stacked Long Short-Term Memory (LSTM) with a pre-training as a regularization method to avoid random network initialization. In our proposal, we use global and short dependencies of the inputs. With pre-training, we avoid random initialization and are able to improve the accuracy and robustness of malware threat hunting. The proposed method speeds up the convergence (in comparison to stacked LSTM) by reducing the length of malware OpCode or bytecode sequences. Hence, the complexity of our final method is reduced. This leads to better accuracy, higher Mattews Correlation Coefficients (MCC), and Area Under the Curve (AUC) in comparison to a standard LSTM with similar detection time. Our proposed method can be applied in real-time malware threat hunting, particularly for safety critical systems such as eHealth or Internet of Military of Things where poor convergence of the model could lead to catastrophic consequences. We evaluate the effectiveness of our proposed method on Windows, Ransomware, Internet of Things (IoT), and Android malware datasets using both static and dynamic analysis. For the IoT malware detection, we also present a comparative summary of the performance on an IoT-specific dataset of our proposed method and the standard stacked LSTM method. More specifically, of our proposed method achieves an accuracy of 99.1% in detecting IoT malware samples, with AUC of 0.985, and MCC of 0.95; thus, outperforming standard LSTM based methods in these key metrics.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.245-251
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• 2022

In this paper, a high gain, broadband planar vivaldi antenna (PVA) by utilizing a broadband stripline feed is developed for wireless communication for IoT systems. The suggested antenna is designed by attaching a tapered-slot construction to a typical vivaldi antenna, which improves the antenna's radiation properties. The PVA is constructed on a low-cost FR4 substrate. The dimensions of the patch are 1.886λ₀×1.42λ₀×0.026λ₀, dielectric constant Ɛ_r=4.4, and loss tangent δ=0.02. The width of the feed line is reduced to improve the impedance bandwidth of the antenna. The computed reflection coefficient findings show that the suggested antenna has a 46.2% wider relative bandwidth calculated at a 10 dB return loss. At the resonance frequencies of 6.5 GHz, the studied results show an optimal gain of 5.82 dBi and 85% optimal radiation efficiency at the operable band. The optometric analysis of the proposed structure shows that the proposed antenna can achieve wide enough bandwidth at the desired frequency and hence make the designed antenna appropriate to work in satellite communication and medical internet of things (M-IoT) healthcare applications.

• Electronics and Telecommunications Trends
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• v.35 no.5
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• pp.43-56
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• 2020

The 5G system standardization body has been developing standard functions to provide ultra-high speed, ultra-high reliability, ultra-low latency, and ultra-connected services. In 3GPP Rel-16, which was recently completed, this system has begun to develop ultra-high reliability and ultra-low latency communication functions to support the vertical industry. It is expected that the trend in the adoption of mobile communication by the vertical industry will continue with the introduction of 5G. In this paper, we present the industrial Internet-of-Things (IIoT) service scenarios and requirements for the adoption of 5G systems by the vertical industry and the related standardization trend at present. In particular, we introduce the 5G time-sensitive networking standard technology, a core technology for realizing 5G-based smart factories, for IIoT services.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.611-612
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• 2017

Recently, exhibition space has incorporated a format in which visual contents providers and viewers can directly or indirectly experience the space with a sense of immersion. By offering more extended spatiality within a limited space, such exhibition design is now transcending physical limitations and expanding to visual reality; as such, exhibition design demands the implementation of not only visual elements but information services generated between people, contents, and objects. To this end, this study examines the changes and the development direction of exhibition techniques that use Internet of Things (IoT), which is a representation of environmental change in exhibition design of our times; it also explores the various forms of change based on the perception of the visual contents (visual exhibits) users during the act of accumulating and using information through the smartphone communication of viewers who experience the space through IoT. Finally, the study conducts a case study on the relationship between a regular exhibition and an exhibition design that makes use of IoT, in order to propose an exhibition design with which to verify whether the viewers are immersed in and experience a sense of realism from visual contents by identifying the viewers' visual and emotional changes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1254-1260
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• 2019

Recently, 5G cellular systems have been attracted great attention as a key enabler for Industry 4.0. In this paper, we propose a novel random access based on pilot-assisted opportunistic transmission to support internet-of-things (IoT) scenario in cellular networks. A key feature of our proposed scheme is to enable each of IoT devices to attempt opportunistic transmission of its data packet in Step 3 with randomly selected uplink pilot signal. Both the opportunistic transmission and the pilot randomization in Step 3 are effective to significantly mitigate the occurrence of packet collisions. We mathematically analyze our proposed scheme in terms of packet collision probability and uplink resource efficiency. Through simulations, we verify the validity of our analysis and evaluate the performance of our proposed scheme. Numerical results show that our proposed scheme outperforms other competitive schemes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.230-238
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• 2022

Internet of Things(IoT) is a communication technology that collects information of object remotely and controls the function of object by adding a communication function to object that does not have a communication function. For the IoT, various communication technologies such as Wi-Fi, 3GPP, and Bluetooth are available, and Long Range(LoRa) is communication technologies specialized in the IoT concept. LoRa is a communication technology that support long-distance, low-power, and low-speed communication, and is suitable for collecting information generated form object in remote equipment and controlling equipment. Because of these characteristics, it is used in many application field, and various performance improvement studies are in progress. This paper intends to propose an ultra-long-range LoRa communication module that can be used in a wider range of applications. We design and implement hardware, firmware, and application software for testing to develop ultra-long-range LoRa communication modules. The implemented module will be tested in a real environment to verify its performance and to check its utilization.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1231-1237
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• 2022

It is necessary to dynamic recognition system with real time loading height and pressure of the loading waste, the drying of wood, batteries, and plastic wastes, which are representative compositional wastes, and the carbonization changes on the surface. The dynamic context awareness service constituted a platform based on Universal Middleware system using BCN convergence communication service as a Ambient SDK model. A context awareness system should be constructed to determine the cause of the fire based on the analysis data of fermentation heat point with natural ignition from the load waste. Furthermore, a real-time dynamic service platform that could be apply to the configuration of scenarios for each type from early warning fire should be built using Universal Middleware. Thus, this issue for Internet of Things realize recognition platform for analyzing low temperature fired fire possibility data should be dynamically configured and presented.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1213-1222
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• 2021

This study is a digitalization study based on ICT technology as part of the development of innovative technologies in the new energy industry as a 2050 carbon-neutral policy. It is the development of an oneM2M-based IoT server platform that can be integrated and managed in conjunction with the external interface of each energy facility. It analyzes KEPCO's e-IoT standard specifications through the Power Research Institute's 'SPIN' and develops representative standards, LWM2M and oneM gateway platforms. OneM2M secures and analyzes the recently announced standard for Release 2 instead of the existing Release 1. In addition, the e-IoT standard oneM2M platform is developed based on R2. In addition, it selects the specifications for e-IoT gateway devices that can sufficiently implement KEPCO's e-IoT standards. In addition, a technology and system for developing a high-performance gateway device that considers future scalability were proposed.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1135-1142
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• 2017

In this paper, we propose IoT based smart CCTV security service to prevent crime in blind spot and prevent unexpected fire or danger. In the proposed method, a RC (Radio Control) car is made using Raspberry pie, and a camera and various modules are installed in an RC car. It was then implemented using Raspbian O / S, Apache Web Server, Shell script, Python, PHP, HTML, CSS, Javascript. The RC car provides a security service that informs the manager of the situation by judging the risk of the scene with modules such as video, voice and temperature. Experimental results show that the transmission time of video and audio information is less than 0.1 second. In addition, real-time status transmission was possible in AVG, emergency, and manual mode. It is expected that the proposed method will be applied to the development of smart city by applying it to unmanned vehicles, drones and the like.

• Journal of Internet of Things and Convergence
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• v.7 no.4
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• pp.1-7
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• 2021

Recently, technological differentiation(sensor, AI) of products using IoT technology to satisfy consumer needs in the mature market for smart home appliances has received a lot of positive responses. However, air conditioner products are in the early stages of convergence technology. Therefore, air conditioner products are fields that require ICT technologies for information production, collection, processing, storage, and service development beyond IoT. In this paper, we collect and store contactless bio-signal using IR-UWB radar technology. The blowing direction of the air conditioning is controlled according to bio-signal and user's sleep is monitored to provide an optimal sleep environment. In addition, we propose a service algorithm that can provide comfort with changes in the optimal conditions of air conditioning and emotional lighting depending on the discomfort index environment. Through this study, we developed an intelligent smart air conditioning service platform with ICT technology of bio-signal, discomfort index, and emotional lighting.