• KIISE Transactions on Computing Practices
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• v.23 no.10
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• pp.579-587
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• 2017

Cyber Mission Impact Assessment is one of the essential tasks which many militaries and industrial major companies should perform to effectively achieve their mission. The unexpected damage to an organization's assets results in damage to the whole system's performance of the organizations. In order to minimize the damage, it is necessary to quantify the available capacity of the mission, which can be achieved only with the remaining assets, and to immediately prepare a new second best plan in a moment. We therefore need to estimate the exact cyber attack's impact to the mission when the unwanted damage occurs by modeling the relationship between the assets and the missions. In this paper, we propose a new model which deals with the dependencies between assets and missions for obtaining the exact impact of a cyber attack. The proposed model distinguishes task management from asset management for an efficient process, and it is implemented to be optimized using a vectorized operation for parallel processing and using a buffer to reduce the computation time.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.2
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• pp.352-364
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• 2017

A novel 3D mathematical model for water film runback and icing on a rotating surface is established in this work, where both inertial forces caused by the rotation and shear forces due to the air flow are taken into account. The mathematical model of the water film runback and energy conservation of phase transition process is established, with a cyclical average method applied to simulate the unsteady parameters variation at angles of attack. Ice accretion on a conical spinner surface is simulated and the results are compared with the experimental data to validate the presented model. Then Ice accretion on a cowling surface is numerically investigated. Results show that a higher temperature would correspond to a larger runback ice area and thinner ice layer for glaze ice. Rotation would enhance the icing process, while it would not significantly affect the droplet collection efficiency for an axi-symmetric surface. In the case at angle of attack, the effect of rotation on ice shape is appreciable, ice would present a symmetric shape, while in a stationary case the shape is asymmetric.

• Journal of Environmental Science International
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• v.21 no.4
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• pp.517-533
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• 2012

This study calculated wind speed at the height of 10 m using a disaster prediction model(Florida Public Hurricane Loss Model, FPHLM) that was developed and used in the United States. Using its distributions, a usable information of surface wind was produced for the purpose of disaster prevention when the typhoon attack. The advanced research version of the WRF (Weather Research and Forecasting) was used in this study, and two domains focusing on South Korea were determined through two-way nesting. A horizontal time series and vertical profile analysis were carried out to examine whether the model provided a resonable simulation, and the meteorological factors, including potential temperature, generally showed the similar distribution with observational data. We determined through comparison of observations that data taken at 700 hPa and used as input data to calculate wind speed at the height of 10 m for the actual terrain was suitable for the simulation. Using these results, the wind speed at the height of 10 m for the actual terrain was calculated and its distributions were shown. Thus, a stronger wind occurred in coastal areas compared to inland areas showing that coastal areas are more vulnerable to strong winds.

• Steel and Composite Structures
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• v.37 no.5
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• pp.589-603
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• 2020

This paper presents an investigation of the thermal performance of composite floor slabs with profiled steel decking exposed to fire effects from floor. A detailed finite-element model has been developed by representing the concrete slab with steel decking under of it and steel beam both steel parts protected by intumescent coating. Although this type of floor systems offers a better fire resistance, passive fire protection materials should be applied when a higher fire resistance is desired. Moreover, fire exposed side is so crucial for composite slab systems as the total fire behaviour of the floor system changes dramatically. When the fire attack from steel parts, the temperature rises rapidly resulting in a sudden decrease on the strength of the beam and decking. Herein this paper, the fire attack side is assumed from the face of the concrete floor (top of the concrete assembly). Therefore, the heat is transferred through concrete to the steel decking and reaching finally to the steel beam both protected by intumescent coating. In this work, the numerical model has been established to predict the heat transfer performance including material properties such as thermal conductivity, specific heat and dry film thickness of intumescent coating. The developed numerical model has been divided into different layers to understand the sensitivity of steel temperature to the number of layers of intumescent coating. Results show that the protected composite floors offer a higher fire resistance as the temperature of the steel section remains below 60℃ even after 60-minute Standard (ISO) fire and Fast fire exposure. Obtaining lower temperatures in steel due to the great fire performance of the concrete itself results in lesser reductions of strength and stiffness hence, lesser deflections.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.107-114
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• 2011

Today the company adopts to use information management method at the network base such as internet, intranet and so on for the speed of business. Therefore the security of information asset protection and continuity of business within company in relation to this is directly connected to the credibility of the company. This paper secures continuity to the certified users using queuing model for the business interruption issue caused by DDoS attack which is faced seriously today. To do this I have reflected overloaded traffic improvement process to the queuing model through the analysis of related traffic information and packet when there occurs DDoS attack with worm/virus. And through experiment I compared and analyzed traffic loading improvement for general network equipment.

• Convergence Security Journal
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• v.20 no.3
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• pp.115-123
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• 2020

Cyber Attack have evolved more and more in recent years. One of the best countermeasure to counter this advanced and sophisticated cyber threat is to predict cyber attacks in advance. It requires a lot of information and effort to predict cyber threats. If we use Open Source Intelligence(OSINT), the core of recent information acquisition, we can predict cyber threats more accurately. In order to predict cyber threats using OSINT, it is necessary to establish a Database(DB) for cyber attacks from OSINT and to select factors that can evaluate cyber threats from the established DB. We are based on previous researches that built a cyber attack DB using data mining and analyzed the importance of core factors among accumulated DG factors by AHP technique. In this research, we present a method for quantifying cyber threats and propose a cyber threats prediction model based on artificial neural networks.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.282-288
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• 2005

In this paper, we propose a new intrusion detection model, which keeps advantages of existing misuse detection model and anomaly detection model and resolves their problems. This new intrusion detection system, named to MMIDS, was designed to satisfy all the following requirements : 1) Fast detection of new types of attack unknown to the system; 2) Provision of detail information about the detected types of attack; 3) cost-effective maintenance due to fast and efficient learning and update; 4) incrementality and scalability of system. The fast and efficient training and updating faculties of proposed novel multi-class SVM which is a core component of MMIDS provide cost-effective maintenance of intrusion detection system. According to the experimental results, our method can provide superior performance in separating similar patterns and detailed separation capability of MMIDS is relatively good.

• The KIPS Transactions:PartC
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• v.18C no.6
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• pp.369-378
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• 2011

To ensure data confidentiality and fine-grained access control in business environment, system model using KP-ABE(Key Policy-Attribute Based Encryption) and PRE(Proxy Re-Encryption) has been proposed recently. However, in previous study, data confidentiality has been effected by decryption right concentrated on cloud server. Also, Yu's work does not consider a access privilege management, so existing work become dangerous to collusion attack between malicious user and cloud server. To resolve this problem, we propose secure system model against collusion attack through dividing data file into header which is sent to privilege manager group and body which is sent to cloud server. And we construct the model of access privilege management using AONT based XOR threshold Secret Sharing, In addition, our scheme enable to grant weight for access privilege using XOR Share. In chapter 4, we differentiate existing scheme and proposed scheme.

• Journal of the Korea Convergence Society
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• v.10 no.5
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• pp.9-16
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• 2019

In this paper, it will analyze security problems, so technology's potential can apply to business security area. First, in order to deep learning do security tasks sufficiently in the business area, deep learning requires repetitive learning with large amounts of data. In this paper, to acquire learning ability to do stable business tasks, it must detect abnormal IP packets and attack such as normal software with malicious code. Therefore, this paper will analyze whether deep learning has the cognitive ability to detect various attack. In this paper, to deep learning to reach the system and reliably execute the business model which has problem, this paper will develop deep learning technology which is equipped with security engine to analyze new IP about Session and do log analysis and solve the problem of mathematical role which can extract abnormal data and distinguish infringement of system data. Then it will apply to business model to drop the vulnerability and improve the business performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2168-2187
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• 2021

The smart grid replaces the traditional power structure with information inventiveness that contributes to a new physical structure. In such a field, malicious information injection can potentially lead to extreme results. Incorrect, FDI attacks will never be identified by typical residual techniques for false data identification. Most of the work on the detection of FDI attacks is based on the linearized power system model DC and does not detect attacks from the AC model. Also, the overwhelming majority of current FDIA recognition approaches focus on FDIA, whilst significant injection location data cannot be achieved. Building on the continuous developments in deep learning, we propose a Deep Learning based Locational Detection technique to continuously recognize the specific areas of FDIA. In the development area solver gap happiness is a False Data Detector (FDD) that incorporates a Convolutional Neural Network (CNN). The FDD is established enough to catch the fake information. As a multi-label classifier, the following CNN is utilized to evaluate the irregularity and cooccurrence dependency of power flow calculations due to the possible attacks. There are no earlier statistical assumptions in the architecture proposed, as they are "model-free." It is also "cost-accommodating" since it does not alter the current FDD framework and it is only several microseconds on a household computer during the identification procedure. We have shown that ANN-MLP, SVM-RBF, and CNN can conduct locational detection under different noise and attack circumstances through broad experience in IEEE 14, 30, 57, and 118 bus systems. Moreover, the multi-name classification method used successfully improves the precision of the present identification.