• Convergence Security Journal
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• v.20 no.5
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• pp.11-17
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• 2020

With the increase in cases of using Bluetooth devices used in the electric vehicle charging systems, security issues are also raised. Although various technical efforts have beed made to enhance security of bluetooth technology, various attack methods exist. In this paper, we propose an intelligent Bluetooth intrusion detection system based on a well-known machine learning method, Hidden Markov Model, for the purpose of detecting intelligently representative Bluetooth attack methods. The proposed approach combines packet types of H4, which is bluetooth transport layer protocol, and the transport directions of the packet firstly to represent the behavior of current traffic, and uses the temporal deployment of these combined types as the final input features for detecting attacks in real time as well as accurate detection. We construct the experimental environment for the data acquisition and analysis the performance of the proposed system against obtained data set.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.975-980
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• 2020

To protect wireless sensor networks (WSNs), various key distribution and management schemes have been proposed. However, most of them conducted simulations and experiments for performance evaluation by considering only the two-dimensional (2D) environments. In this paper, we investigate the effect of real-world three-dimensional (3D) topographic features on the key pre-distribution schemes for WSNs. For this purpose, we analyze and compare the performance of three pairwise key pre-distribution schemes in 2D and 3D environments: full pairwise (FP), random pairwise (RP), and full and random pairwise (FRP) schemes. For the experiments, we employ a network simulator NS-3 and 3D graphic tools such as Blender and Unity. As a result, we confirm that there was a difference in the performance of each scheme according to the actual 3D terrain and that the location-based FRP that considers deployment errors, has the highest efficiency in many aspects.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1141-1149
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• 2020

Most of the industrial control network is an independent closed network, which is operated for a long time after installation, and thus the OS is not updated, so security threats increase and security vulnerabilities exist. The zero-day attack defense must be applied with the latest patch, but in a large-scale industrial network, it requires a higher level of real-time and non-disruptive operation due to the direct handling of physical devices, so a step-by-step approach is required to apply it to a live system. In order to solve this problem, utility-specific patch impact assessment is required for reliable patch application. In this paper, we propose a method to test and safely install the patch using the regression analysis technique and show the proven results. As a patch impact evaluation methodology, the maximum allowance for determining the safety of a patch was derived by classifying test types based on system-specific functions, performance, and behavior before and after applying the patch. Finally, we report the results of case studies applied directly to industrial control networks, the OS patch has been updated while ensuring 99.99% availability.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.451-457
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• 2020

Diverse sensors are equipped on P-3C Maritime Patrol Aircraft for RoKN to detect and monitor tactical targets. Tactical targets are maintained/shared by tactical computer stations which consist of a clustering network in the aircraft and displayed in various ways on TSDs(Tactical Situation Displays) for mission operators to perform their specified missions. Korea peninsula is widely covered with the sea areas and neighboured with several countries; which makes huge number of ships and aircraft deployment around the place. Due to an increase in number of sensors and enhancement of their sensitivities; we were aware of the necessity of TSD improvements to provide huge number of tactical targets and to display them efficiently. In this paper, we propose a solution for the improvements by using previous backup data and re-usage of the data, then we verify the proposal through implementation and evaluation results.

• Journal of Advanced Navigation Technology
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• v.25 no.4
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• pp.267-272
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• 2021

The end of the ROK-U.S. missile guidelines opened up the possibility of developing space launch vehicles for various platforms based on air and sea. In particular, the air-based space launch vehicle is an essential space power projection capability compared to the ground-based space launch vehicle in consideration of the geographical location of the Korean Peninsula, such as the deployment of various satellite orbits and the timely launch of satellite. In addition, compared to the ground-based launch vehicle, the cost reduction effect is large, and it has the merit of energy gain because it can be launched with the advantage of the aircraft's altitude and speed. Therefore, in this paper, the necessity of air-based space launch vehicle in the strategic environment of the Korean Peninsula is clearly presented, and through technology trend analysis of various air launch vehicle, the three methods are proposed to have the most efficient air-based space launch vehicle capability in the Korean situation.

• Research in Plant Disease
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• v.27 no.4
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• pp.137-148
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• 2021

Plant RNA viruses are one of the most destructive pathogens that cause a significant loss in crop production worldwide. They have evolved with high genetic diversity and adaptability due to the short replication cycle and high mutation rate during genome replication, which are characteristics of RNA viruses. Plant RNA viruses exist as quasispecies with high genetic diversity; thereby, a rapid population transition with new fitness can occur due to selective pressure resulting from environmental changes. Plant resistance can act as selective pressure and affect the fitness of the virus, which may lead to the emergence of resistance-breaking variants. In this paper, we introduced the evolutionary perspectives of plant RNA viruses and the driving forces in their evolution. Based on this, we discussed the mechanism of the emergence of variant viruses that overcome plant resistance. In addition, strategies for deploying plant resistance to viral diseases and improving resistance durability were discussed.

• The Plant Pathology Journal
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• v.38 no.4
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• pp.313-322
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• 2022

Seed-borne pathogens in crops reduce the seed germination rate and hamper seedling growth, leading to significant yield loss. Due to the growing concerns about environmental damage and the development of resistance to agrochemicals among pathogen populations, there is a strong demand for eco-friendly alternatives to synthetic chemicals in agriculture. It has been well established during the last few decades that plant seeds harbor diverse microbes, some of which are vertically transmitted and important for plant health and productivity. In this study, we isolated culturable endophytic bacteria and fungi from soybean seeds and evaluated their antagonistic activities against common bacterial and fungal seed-borne pathogens of soybean. A total of 87 bacterial isolates and 66 fungal isolates were obtained. Sequencing of 16S rDNA and internal transcribed spacer amplicon showed that these isolates correspond to 30 and 15 different species of bacteria and fungi, respectively. Our antibacterial and antifungal activity assay showed that four fungal species and nine bacterial species have the potential to suppress the growth of at least one seed-borne pathogen tested in the study. Among them, Pseudomonas koreensis appears to have strong antagonistic activities across all the pathogens. Our collection of soybean seed endophytes would be a valuable resource not only for studying biology and ecology of seed endophytes but also for practical deployment of seed endophytes toward crop protection.

• Journal of Korean Neurosurgical Society
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• v.65 no.4
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• pp.523-530
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• 2022

Objective : To evaluate the safety and efficacy of an overlapped stenting-assisted coiling technique in treating vertebral artery dissecting aneurysm (VADA) via Low-profile Visualized Intraluminal Support (LVIS) stent-within-Neuroform EZ stent. Methods : From January 2017 to June 2019, 18 consecutive patients with VADAs (ruptured : unruptured=5 : 13) were treated with the overlapping stents assisted-coiling technique in our center. The overlapping manner was a Neuroform EZ stent being deployed first, followed by LVIS stents placement using the 'shelf' technique. The patients' clinical characteristics, technical feasibility and safety, and immediate and follow-up angiographic results were retrospectively reviewed. Results : Seventeen (94.4%) procedures were technically successful with an exact deployment of the stents and patent parent or perforator arteries. The immediate angiographies after procedure confirmed Raymond class I, II, and III occlusion of VADAs were in 12 (66.7%), two (11.1%), and four cases (22.2%), respectively. Post-procedural complications developed in one patient (5.6%) with minor brainstem infarctions, which resulted from an in-stent thrombosis during the procedure. Angiographic follow-up at 5.7 months (range 3 to 9 months) demonstrated Raymond class I and II occlusion were in all cases (100%). The modified Rankin Scale scores at 21.3 months (range 15 to 42 months) 0-2 in 17 cases (94.4%) and three in one case (5.6%). Conclusion : Overlapping stents via LVIS stent-within-Neuroform EZ stent combined with coiling is safe and effective for patients with VADA in the midterm results.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.99-104
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• 2022

Artificial intelligence is getting a crucial part of our lives with its incredible benefits. Machines outperform humans in recognizing objects in images, particularly in classifying people into correct age and gender groups. In this respect, age and gender classification has been one of the hot topics among computer vision researchers in recent decades. Deployment of deep Convolutional Neural Network(: CNN) models achieved state-of-the-art performance. However, the most of CNN based architectures are very complex with several dozens of training parameters so they require much computation time and resources. For this reason, we propose a new CNN-based classification algorithm with significantly fewer training parameters and training time compared to the existing methods. Despite its less complexity, our model shows better accuracy of age and gender classification on the UTKFace dataset.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1432-1440
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• 2022

Recently, as Virtual Desktop Infrastructure(VDI) is widely used not only in office work environments but also in workloads that use high-spec multi-core-based applications, the requirements for real-time and stability of VDI are increasing. Accordingly, the display protocol used for remote access in VDI and performance optimization of virtual machines have also become more important. In this paper, we propose two ways to configure desktop virtualization for multi-core-based application operation. First, we propose a codec configuration of a display protocol with optimal performance in a high load situation due to multi-processing. Second, we propose a virtual CPU scheduling optimization method to reduce scheduling delay in case of CPU contention between virtual machines. As a result of the test, it was confirmed that the H.264 codec of Blast Extreme showed the best and stable frame, and the scheduling performance of the virtual CPU was improved through scheduling optimization.