• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.3
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• pp.491-498
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• 2014

Recently, cyber terror has been occurred frequently based on advanced persistent threat(APT) and it is very difficult to detect these attacks because of new malwares which cannot be detected by anti-virus softwares. This paper proposes and verifies the algorithms to detect the advanced persistent threat previously through real-time network monitoring and combinatorial analysis of big data log. In the future, APT attacks can be detected more easily by enhancing these algorithms and adapting big data platform.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.1
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• pp.241-269
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• 2012

Wireless networks composed of multimedia-enabled resource-constrained sensor nodes have enriched a large set of monitoring sensing applications. In such communication scenario, however, new challenges in data transmission and energy-efficiency have arisen due to the stringent requirements of those sensor networks. Generally, congested nodes may deplete the energy of the active congested paths toward the sink and incur in undesired communication delay and packet dropping, while bit errors during transmission may negatively impact the end-to-end quality of the received data. Many approaches have been proposed to face congestion and provide reliable communications in wireless sensor networks, usually employing some transport protocol that address one or both of these issues. Nevertheless, due to the unique characteristics of multimedia-based wireless sensor networks, notably minimum bandwidth demand, bounded delay and reduced energy consumption requirement, communication protocols from traditional scalar wireless sensor networks are not suitable for multimedia sensor networks. In the last decade, such requirements have fostered research in adapting existing protocols or proposing new protocols from scratch. We survey the state of the art of transport protocols for wireless multimedia sensor networks, addressing the recent developments and proposed strategies for congestion control and loss recovery. Future research directions are also discussed, outlining the remaining challenges and promising investigation areas.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.1
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• pp.203-228
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• 2012

It is expected that device-to-device (D2D) communication is allowed to underlay future cellular networks such as IMT-Advanced for spectrum efficiency. This article studies the mechanisms of D2D communication and interference avoidance when the D2D subsystem reuses uplink resources and downlink spectrums with a cellular system, respectively. We firstly propose an effective scheme to establish and maintain D2D communication. Moreover, a novel method to deal with the resource allocation and interference avoidance issues by utilizing the network peculiarity of a hybrid network to share the uplink resource is proposed. Most research focuses on reusing the uplink spectrums, but how to share the downlink frequency bands is seldom addressed. To share the downlink spectrums and avoid the interference to the primary cellular devices, a labeled time slots based mechanism is proposed. Implementation details are described in a real cellular system and simulation results prove that satisfying performance can be achieved by using the proposed mechanisms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.4061-4076
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• 2017

With the development of high-speed railway technologies, train velocities can now reach speeds up to 350 km/h, and higher in the future. In high-speed railway systems (HSRs), loss of communication can result in serious accidents, especially when the train is controlled through wireless communications. For to this reason, operators of Long Term Evolution for Railway (LTE-R) communication systems install eNodeBs (eNBs) with high density to achieve highly reliable communications. However, densely located eNBs can result in unnecessary frequent handovers (HOs) resulting in instability because, during every HO process, there is a period of time in which the communication link is disconnected. To solve this problem, in this paper, an HO scheme based on the maximum cell residence time (CRT) and adaptive time to trigger (aTTT), which are collectively called CaT, is proposed to reduce unnecessary HOs (using CRT estimations) and decrease HO failures by improving the handover command transmission point (HCTP) in LTE-R HSR communications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.1912-1931
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• 2018

In future wireless network, user experience and energy efficiency will play more and more important roles in the communication systems compared to their roles at present. Quality of experience (QoE) and Energy Efficiency (EE) become the widely used metrics. In this paper, we study a combinatorial problem of QoE and EE and investigate a fair power allocation in heterogeneous networks. We first design a new metric, QoE-aware EE (QEE) to reflect the relationship of QoE and energy. Then, the concept of Utopia QEE is introduced, which is defined as the achievable maximum QEE in ideal conditions, for each user. Finally, we transform the power allocation process to an optimization of ratio of QEE and Utopia QEE and use invasive weed optimization (IWO) algorithm to solve the optimization problem. Numerical simulation results indicate that the proposed algorithm can get converged and efficiently improve the system energy efficiency and the QoE for each user.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.743-749
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• 2020

Internet of Things (IoT) is a growing technology along with artificial intelligence (AI) technology. Recently, increasing cases of developing knowledge services using information collected from sensor data have been reported. Communication is required to connect the IoT and AI, and 5G mobile networks have been widely spread recently. IoT, AI services, and 5G mobile networks can be configured and used as sensor-mobile edge-server. The sensor does not send data directly to the server. Instead, the sensor sends data to the mobile edge for quick processing. Subsequently, mobile edge enables the immediate processing of data based on AI technology or by sending data to the server for processing. 5G mobile network technology is used for this data transmission. Therefore, this study examines the challenges, opportunities, and solutions used in each type of technology. To this end, this study addresses clustering, Hyperledger Fabric, data, security, machine vision, convolutional neural network, IoT technology, and resource management of 5G mobile networks.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.37-42
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• 2019

In this paper, we explore the details of three classic data augmentation methods and two generative model based oversampling methods. The three classic data augmentation methods are random sampling (RANDOM), Synthetic Minority Over-sampling Technique (SMOTE), and Adaptive Synthetic Sampling (ADASYN). The two generative model based oversampling methods are Conditional Generative Adversarial Network (CGAN) and Wasserstein Generative Adversarial Network (WGAN). In imbalanced data, the whole instances are divided into majority class and minority class, where majority class occupies most of the instances in the training set and minority class only includes a few instances. Generative models have their own advantages when they are used to generate more plausible samples referring to the distribution of the minority class. We also adopt CGAN to compare the data augmentation performance with other methods. The experimental results show that WGAN-based oversampling technique is more stable than other approaches (RANDOM, SMOTE, ADASYN and CGAN) even with the very limited training datasets. However, when the imbalanced ratio is too small, generative model based approaches cannot achieve satisfying performance than the conventional data augmentation techniques. These results suggest us one of future research directions.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.34 no.6
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• pp.475-479
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• 2021

There are many difficulties in the applications of smart manufacturing technology in the era of the 4th industrial revolution. In this paper, a test bed was built to aim for acquiring smart manufacturing technology, and the test bed was designed to acquire basic technologies necessary for PLC (Programmable Logic Controller), HMI, Internet of Things (IoT), artificial intelligence (AI) and big data. By building a vehicle maintenance lift that can be easily accessed by the general public, PLC control technology and HMI drawing technology can be acquired, and by using cloud services, workers can respond to emergencies and alarms regardless of time and space. In addition, by managing and monitoring data for smart manufacturing, it is possible to acquire basic technologies necessary for embedded systems, the Internet of Things, artificial intelligence, and big data. It is expected that the improvement of smart manufacturing technology capability according to the results of this study will contribute to the effect of creating added value according to the applications of smart manufacturing technology in the future.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.1-9
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• 2021

In the Internet of Thing (IoT) framework, massive machine-type communications (MMTC) have required large spectral efficiency. For this, non-orthogonal multiple access (NOMA) has emerged as an efficient solution. Recently, a non-successive interference cancellation (SIC) NOMA scheme has been implemented without loss. This lossless NOMA without SIC is achieved via correlated superposition coding (SC), in contrast to conventional independent SC. However, conventional minimum high-correlated SC for only 2-user NOMA schemes was investigated in the lossless 2-user non-SIC NOMA implementation. Thus, this paper investigates a 3-user low-correlated SC scheme, especially for an inflated achievable sum rate, with a design of 3-user low-correlated SC. First, we design the 3-user low-correlated SC scheme by taking the minimum sum rate between 3-user SIC NOMA and 3-user non-SIC NOMA, both with correlated SC. Then, simulations demonstrate that the low correlation in the direction of the first user's power allocation inflates the sum rate in the same direction, compared to that of conventional minimum high-correlated SC NOMA, and such inflation due to low correlation is also observed similarly, in the direction of the second user's power allocation. Moreover, we also show that the two low correlations of the first and second users inflates doubly in the both directions of the first and second users' power allocations. As a result, the proposed 3-user low-correlated SC could be considered as a promising scheme, with the inflated sum rate in the future fifth-generation (5G) NOMA networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.3025-3047
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• 2021

This paper presents the latest Ethernet standardization of in-vehicle network and the future trends of automotive Ethernet technology. The proposed system provides design and optimization algorithms for automotive networking technology related to AVB (Audio Video Bridge) technology. We present a design of in-vehicle network system as well as the optimization of AVB for automotive. A proposal of Reduced Latency of Machine to Machine (RLMM) plays an outstanding role in reducing the latency among devices. RLMM's approach to real-world experimental cases indicates a reduction in latency of around 41.2%. The setup optimized for the automotive network environment is expected to significantly reduce the time in the development and design process. The results obtained in the study of image transmission latency are trustworthy because average values were collected over a long period of time. It is necessary to analyze a latency between multimedia devices within limited time which will be of considerable benefit to the industry. Furthermore, the proposed reliable camera and video streaming through optimized AVB device settings would provide a high level of support in the real-time comprehension and analysis of images with AI (Artificial Intelligence) algorithms in autonomous driving.