• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.54 no.4
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• pp.343-352
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• 2018

In this study, a motion control problem for the vessels towed by tugboats or towing ships on the sea is considered. The towed vessel looks like the barge ship, which is used for many purposes. In these vessels, basically, the power propulsion system is not installed but just towed by a towing vessel such as tugboats with ropes and wires. It means that the motions of towed vessel are basically dependent on the tracking route of towing boat. Therefore, in some cases, undesirable and unpredictable motions may be made by environmental factors such as wave, wind attack and so on. As a result, a collision accident with others may occur during maneuvering situation. Based on these facts, the authors try to encourage the steering performance of the towed vessel by using controllable rudders without any propulsion system. In this study, especially, a controllable vessel with three rudders is considered, and a mathematical model is induced for the future study. The model is described as surge, sway motion and inertia moment by following the general representation method for the surface ship.

• Journal of the Korea Society for Simulation
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• v.30 no.1
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• pp.1-9
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• 2021

In actual battlefield environment, the naval ships which have specific missions have to respond to the attack of hostile forces. Especially, in modern warfare, the importance of the survivability of naval ships are increasing due to the high lethality of armaments. Naval ship survivability is generally considered to encompass three constituents, susceptibility, vulnerability and recoverability. Recently, among these three constituents, many researches on vulnerability have been conducted. However, for the vulnerability of naval ships, most of researches are aimed towards the detailed design stages where implementing changes is heavily constrained or even impractical. In this paper, vulnerability assessment model for naval ships on a theater engagement is developed by using M&S technique. By using this model, the characteristics of platform and armaments are reflected on the damage of naval ship. The basic logic of damage assessment is also considered in detail. The damage status of the naval ship is quantified by defining a representative state index of onboard equipment for each system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.281-288
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• 2024

The sixth generation(6G) wireless communication technology is advancing toward ultra-high speed, ultra-high bandwidth, and hyper-connectivity. With the development of communication technologies, the formation of a hyper-connected society is rapidly accelerating, expanding from the IoT(Internet of Things) to the IoE(Internet of Everything). However, at the same time, security threats targeting IoT devices have become widespread, and there are concerns about security incidents such as unauthorized access and information leakage. As a result, the need for security-enhancing solutions is increasing. In this paper, we implement an autoencoder-based anomaly detection model utilizing real-time collected network traffics in respond to IoT security threats. Considering the difficulty of capturing IoT device traffic data for each attack in real IoT environments, we use an unsupervised learning-based autoencoder and implement 6 different autoencoder models based on the use of noise in the training data and the dimensions of the latent space. By comparing the model performance through experiments, we provide a performance evaluation of the anomaly detection model for detecting abnormal network traffic.

• Journal of IKEEE
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• v.28 no.1
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• pp.6-13
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• 2024

This paper proposes an approach to detect abnormal data in automotive controller area network (CAN) using an unsupervised learning model, i.e. autoencoder and Gaussian kernel density estimation function. The proposed autoencoder model is trained with only message ID of CAN data frames. Afterwards, by employing the Gaussian kernel density estimation function, it effectively detects abnormal data based on the trained model characterized by the optimally determined number of frames and a loss threshold. It was verified and evaluated using four types of attack data, i.e. DoS attacks, gear spoofing attacks, RPM spoofing attacks, and fuzzy attacks. Compared with conventional unsupervised learning-based models, it has achieved over 99% detection performance across all evaluation metrics.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.301-313
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• 2020

This study is a study on the interlocking method between emergency preparedness simulation model and military exercise war game model. The national emergency preparedness government exercises are being carried out by a message exercise and technology development for simulation models is being carried out to create a situation similar to the actual practice. In order to create a situation similar to the actual war, the military situation must be reflected and to do so, a link with the military exercise war game model is needed. The military exercise war game model applies HLA/RTI, which is a standardized interlocking method for various models such as Taegeuk JOS, and it is necessary to apply HLA/RTI linkage method to link with these military exercise war game models. In addition, since the emergency preparedness simulation model requires limited information such as enemy location and enemy attack situation on major facilities in the military exercise model, a method of interlocking that can select and link information is required. Therefore, in this study, the interlocking interface design plan is presented in order to selectively link the interlocking method and information between the emergency preparedness simulation model and the military exercise war game model. The main functions of interlocking interface include federation synchronization, storage and recovery, object management service, time management, and data filtering functions.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.27 no.4
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• pp.278-285
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• 1991

The authors propose to use the slot system in order to improve of the efficiency for the cambered otter boards. The experiment is divided into 2 parts, one is the efficiency model test, and the other is the visualization model test. The hydrodynamic characteristics of the model otter boards were tested by efficiency model test to measure the shearing, drag force of the models and visualization test using hydrogen bubble method to observe the streak-line and time-line of flow around the models, and milk spout method to observe the separation zone in the wake behind the models. This study tested for 5 models such ad without slot, slot position 0.2C, 0.4C, 0.6C and 0.8C. The results obtained are as follows: \circled1 The maximum C sub(L) of model otter board with slot position 0.6C in attack angle 27$^{\circ}$ was the highest of all models, it's value was 1.59. \circled2 In general, the L/D ratio of the one slot otter boards were 16~28% higher than otter board without slot. \circled3 The slot position 0.6C was better than any other slot position, and it's conformed by visiualization. \circled4 As to the model otter board with slot position 0.6C, flow speed of the back side was faster 1.3 to 1.7 times than in the front side. \circled5 The size of the separated zone in case of the model otter board with 0.6C was smaller than that of any other models.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.896-905
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• 2021

In the field of SIEM(Security information and event management), many studies try to use a feedback system to solve lack of completeness of training data and false positives of new attack events that occur in the actual operation. However, the current feedback system requires too much human inputs to improve the running model and even so, those feedback from inexperienced analysts can affect the model performance negatively. Therefore, we propose "active model improving feedback technology" to solve the shortage of security analyst manpower, increasing false positive rates and degrading model performance. First, we cluster similar predicted events during the operation, calculate feedback priorities for those clusters and select and provide representative events from those highly prioritized clusters using XAI (eXplainable AI)-based event visualization. Once these events are feedbacked, we exclude less analogous events and then propagate the feedback throughout the clusters. Finally, these events are incrementally trained by an existing model. To verify the effectiveness of our proposal, we compared three distinct scenarios using PKDD2007 and CSIC2012. As a result, our proposal confirmed a 30% higher performance in all indicators compared to that of the model with no feedback and the current feedback system.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.2
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• pp.112-124
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• 2004

A neural network based adaptive reconfigurable flight controller is presented for a class of discrete-time nonlinear flight systems in the presence of variations of aerodynamic coefficients and control effectiveness decrease caused by control surface damage. The proposed adaptive nonlinear controller is developed making use of the backstepping technique for the angle of attack, sideslip angle, and bank angle command following without two time separation assumption. Feedforward multilayer neural networks are implemented to guarantee reconfigurability for control surface damage as well as robustness to the aerodynamic uncertainties. The main feature of the proposed controller is that the adaptive controller is developed under the assumption that all of the nonlinear functions of the discrete-time flight system are not known accurately, whereas most previous works on flight system applications even in continuous time assume that only the nonlinear functions of fast dynamics are unknown. Neural networks learn through the recursive weight update rules that are derived from the discrete-time version of Lyapunov control theory. The boundness of the error states and neural networks weight estimation errors is also investigated by the discrete-time Lyapunov derivatives analysis. To show the effectiveness of the proposed control law, the approach is i]lustrated by applying to the nonlinear dynamic model of the high performance aircraft.

• The KIPS Transactions:PartC
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• v.10C no.3
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• pp.253-264
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• 2003

This paper presents the analytic model of Distributed Denial-of-Service (DDoS) attacks in two settings: the normal Web server without any attack and the Web server with DDoS attacks. In these settings, we measure TCP flag rate, which is expressed in terms of the ratio of the number of TCP flags, i.e., SYN, ACK, RST, etc., packets over the total number of TCP packets, and Protocol rate, which is defined by the ratio of the number of TCP (UDP or ICMP) packets over the total number of W packets. The experimental results show a distinctive and predictive pattern of DDoS attacks. We wish our approach can be used to detect and prevent DDoS attacks.

• 한국균학회소식:학술대회논문집
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• 2015.05a
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• pp.54-54
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• 2015

Crops lack genetic resistance to most necrotrophic soil-borne pathogens and parasitic nematodes that are ubiquitous in agroecosystems worldwide. To overcome this disadvantage, plants recruit and nurture specific group of antagonistic microorganisms from the soil microbiome to defend their roots against pathogens and other pests. The best example of this microbe-based defense of roots is observed in disease-suppressive soils in which the suppressiveness is induced by continuously growing crops that are susceptible to a pathogen. Suppressive soils occur globally yet the microbial basis of most is still poorly described. Fusarium wilt, caused by Fusarium oxysporum f. sp. fragariae is a major disease of strawberry and is naturally suppressed in Korean fields that have undergone continuous strawberry monoculture. Here we show that members of the genus Streptomyces are the specific bacterial components of the microbiome responsible for the suppressiveness that controls Fusarium wilt of strawberry. Furthermore, genome sequencing revealed that Streptomyces griseus, which produces a novel thiopetide antibiotic, is the principal species involved in the suppressiveness. Finally, chemical-genetic studies demonstrated that S. griseus antagonizes F. oxysporum by interfering with fungal cell wall synthesis. An attack by F. oxysporum initiates a defensive "cry for help" by strawberry root and the mustering of microbial defenses led by Streptomyces. These results provide a model for future studies to elucidate the basis of microbially-based defense systems and soil suppressiveness from the field to the molecular level.