• Journal of the Korea Institute of Information Security & Cryptology
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• v.9 no.1
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• pp.71-84
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• 1999

The most of intrusion detection methods do not detect intrusion when it happens. To solve the problem, we are studying a real-time intrusion detection. Because a previous intrusion detection system(IDS) is running on the host level, it difficult to port and to extend to other system on the network level that distributed environment. Also IDS provides the confidentiality of messages when it sends each other. This paper proposes a model of real-time intrusion detection using agents. It applies to distributed environment using an extensibility and communication mechanism among agents, supports a portability, an extensibility and a confidentiality of IDS.

• Smart Structures and Systems
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• v.10 no.3
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• pp.229-251
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• 2012

Guided waves have shown a great potential for structural health monitoring (SHM) applications. In contrast to traditional non-destructive testing (NDT) methodologies, a key element of SHM approaches is the high process of automation. The monitoring system should decide autonomously whether the host structure is intact or not. A basic requirement for the realization of such a system is that the sensors are permanently installed on the host structure. Thus, baseline measurements become available that can be used for diagnostic purposes, i.e., damage detection, localization, etc. This paper contributes to guided wave-based inspection in anisotropic materials for SHM purposes. Therefore, computational strategies are described for both, the solution of the complex equations for wave propagation analysis in composite materials based on exact elasticity theory and the popular global matrix method, as well as the underlying equations of two active damage localization algorithms for anisotropic structures. The result of the global matrix method is an angular and frequency dependent wave velocity characteristic that is used subsequently in the localization procedures. Numerical simulations and experimental investigations through time-delay measurements are carried out in order to validate the proposed theoretical model. An exemplary case study including the calculation of dispersion curves and damage localization is conducted on an exemplary unidirectional composite structure where the ultrasonic signals processed in the localization step are simulated with the spectral element method. The proposed study demonstrates the capabilities of the proposed algorithms for accurate damage localization in anisotropic structures.

• The Journal of the Korea Contents Association
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• v.19 no.10
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• pp.620-629
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• 2019

An automated minutes summary system is required to objectively summarize and classify the contents of discussions or discussions for decision making. This paper designs and implements a minutes summary system using word2vec model to complement the existing minutes summary system. The proposed system is further implemented with word2vec model to remove index words during morpheme analysis and to extract representative sentences with common opinions from documents. The proposed system automatically classifies documents collected during the meeting process and extracts representative sentences representing the agenda among various opinions. The conference host can quickly identify and manage all the agendas discussed at the meeting through the proposal system. The proposed system analyzes various agendas of large-scale debates or discussions and summarizes sentences that can be representative opinions to support fast and accurate decision making.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.2
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• pp.68-78
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• 1995

Until now, the electrical monitoring system had been used of the Graphic-Mosaic panel, which is located to the cellar at the apartment complex. it was inappropriated to man-power and system-organization at apartment complex. for that reason, in this paper IMS is presented. An Intelligent Monitoring System can provide and explanation of real-time opera- state of an electric power apparatus to its operators in apartment complex. IMS is proposed as a model for integration supervisory system whose primary tasks are to communicate line data with host-computer and slave-controller it is based on a generalized version of use-career and a trouble shoot knowledge base for diagnostic problem solving. to operate it, both of controller and its operator-view is deigned by the real-tune O.S TREND 940.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.179-191
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• 2024

With the advancement of modern technology, cyber-attacks are always rising. Specialized defense systems are needed to protect organizations against these threats. Malicious behavior in the network is discovered using security tools like intrusion detection systems (IDS), firewall, antimalware systems, security information and event management (SIEM). It aids in defending businesses from attacks. Delivering advance threat feeds for precise attack detection in intrusion detection systems is the role of cyber-threat intelligence (CTI) in the study is being presented. In this proposed work CTI feeds are utilized in the detection of assaults accurately in intrusion detection system. The ultimate objective is to identify the attacker behind the attack. Several data sets had been analyzed for attack detection. With the proposed study the ability to identify network attacks has improved by using machine learning algorithms. The proposed model provides 98% accuracy, 97% precision, and 96% recall respectively.

• Smart Structures and Systems
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• v.5 no.3
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• pp.241-260
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• 2009

Shape control of flexible structures using piezoelectric materials has attracted much attention due to its wide applications in controllable systems such as space and aeronautical engineering. The major work in the field is to find a best control voltage or an optimal placement of the piezoelectric actuators in order to actuate the structure shape as close as possible to the desired one. The current research focus on the investigation of static shape control of intelligent shells using spatially distributed piezoelectric curve beam actuators. The finite element formulation of the piezoelectric model is briefly described. The piezoelectric curve beam element is then integrated into a collocated host shell element by using nodal displacement constraint equations. The linear least square method (LLSM) is employed to get the optimum voltage distributions in the control system so that the desired structure shape can be well matched. Furthermore, to find the optimal placement of the piezoelectric curve beam actuators, a genetic algorithm (GA) is introduced in the computation model as well as the consideration of the different objective functions. Numerical results are given to demonstrate the validity of the theoretical model and numerical algorithm developed.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.924-935
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• 2023

Purpose: The central aim of this study is to leverage machine learning techniques for the classification of Intrusion Detection System (IDS) data, with a specific focus on identifying the variables responsible for enhancing overall performance. Method: First, we classified 'R2L(Remote to Local)' and 'U2R (User to Root)' attacks in the NSL-KDD dataset, which are difficult to detect due to class imbalance, using seven machine learning models, including Logistic Regression (LR) and K-Nearest Neighbor (KNN). Next, we use the SHapley Additive exPlanation (SHAP) for two classification models that showed high performance, Random Forest (RF) and Light Gradient-Boosting Machine (LGBM), to check the importance of variables that affect classification for each model. Result: In the case of RF, the 'service' variable and in the case of LGBM, the 'dst_host_srv_count' variable were confirmed to be the most important variables. These pivotal variables serve as key factors capable of enhancing performance in the context of classification for each respective model. Conclusion: In conclusion, this paper successfully identifies the optimal models, RF and LGBM, for classifying 'R2L' and 'U2R' attacks, while elucidating the crucial variables associated with each selected model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.658-661
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• 2008

As network security is coming up with significant problem after the major Internet sites were hacked nowadays, IDS(Intrusion Detection System) is considered as a next generation security solution for more trusted network and system security. We propose the new IDS model which can detect intrusion in the expanded distribute environment in host level, drawback of existing IDS, and implement prototype. We used pattern extraction agent so that we extract automatically audit file needed in intrusion detection even in other platforms.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1892-1900
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• 2023

A protective oxide layer forms on the material surfaces of a Nuclear Power Plant during operation due to high temperature. These oxides can host radionuclides, the activated corrosion products of fission products, resulting in decommissioning workers' exposure. These deposited oxides are iron oxides such as Fe₃O₄, Fe₂O₃ and mixed ferrites such as nickel ferrites, chromium ferrites, and cobalt ferrites. Developing a new chemical decontamination technology for domestic CANDU-type reactors is challenging due to variations in oxide compositions from different structural materials in a Pressurized Water Reactor (PWR) system. The Korea Atomic Energy Research Institute (KAERI) has already developed a chemical decontamination process for PWRs called 'HyBRID' (Hydrazine-Based Reductive metal Ion Decontamination) that does not use organic acids or organic chelating agents at all. As the first step to developing a new chemical decontamination technology for the Pressurized Heavy Water Reactor (PHWR) system, we investigated magnetite dissolution behaviors in various HyBRID inorganic acidic solutions to assess their applicability to the PHWR reactor system, which forms a thicker oxide film.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1066-1072
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• 2011

In the method to analyze the relationship in the system call orders, the normal system call orders are divided into a certain size of system call orders to generates gene and use them as the detectors. In the method to consider the system call parameters, the mean and standard deviation of the parameter lengths are used as the detectors. The attack of which system call order is normal but the parameter values are changed, such as the format string attack, cannot be detected by the method that considers only the system call orders, whereas the model that considers only the system call parameters has the drawback of high positive defect rate because of the information obtained from the interval where the attack has not been initiated, since the parameters are considered individually. To solve these problems, it is necessary to develop a more efficient learning and detecting method that groups the continuous system call orders and parameters as the approach that considers various characteristics of system call related to attacking simultaneously. In this article, we detected the anomaly of the system call orders and parameters by applying the temporal concept to the system call orders and parameters in order to improve the rate of positive defect, that is, the misjudgment of anomaly as normality. The result of the experiment where the DARPA data set was employed showed that the proposed method improved the positive defect rate by 13% in the system call order model where time was considered in comparison with that of the model where time was not considered.