• Journal of the Korea Society for Simulation
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• v.8 no.1
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• pp.89-99
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• 1999

The major objective of this research is to propose a design architecture for autonomous defense systems for supporting highly intelligent behavior by combining decision, perception, and action components. Systems with such high levels of autonomy are critical for advanced battlefield missions. By integrating a plenty of advanced modeling concepts such as system entity structure, endomorphic modeling, engine-based modeling, and hierarchical encapsulation & abstraction principle, we have proposed four layered design methodology for autonomous defense systems that can support an intelligent behavior under the complicated and unstable warfare. Proposed methodology has been successfully applied to a design of autonomous tank systems capable of supporting the autonomous planning, sensing, control, and diagnosis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.5062-5079
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• 2017

Malicious insider threats have increased recently, and methods of the threats are diversifying every day. These insider threats are becoming a significant problem in corporations and governments today. From a technology standpoint, detecting potential insider threats is difficult in early stage because it is unpredictable. In order to prevent insider threats in early stage, it is necessary to collect all of insiders' data which flow in network systems, and then analyze whether the data are potential threat or not. However, analyzing all of data makes us spend too much time and cost. In addition, we need a large repository in order to collect and manage these data. To resolve this problem, we develop an indicator-based behavior ontology (IB2O) that allows us to understand and interpret insiders' data packets, and then to detect potential threats in early stage in network systems including social networks and company networks. To show feasibility of the behavior ontology, we developed a prototype platform called Insider Threat Detecting Extractor (ITDE) for detecting potential insider threats in early stage based on the behavior ontology. Finally, we showed how the behavior ontology would help detect potential inside threats in network system. We expect that the behavior ontology will be able to contribute to detecting malicious insider threats in early stage.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.229-235
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• 2003

We designed a family of completely autonomous mobile robots with local intelligence. Each robot has a number of on-board sensors, including vision, and does not rely on global positioning systems The on-board embedded controller is sufficient to analyze several low-resolution color images per second. This enables our robots to perform several complex tasks such as navigation, map generation, or providing intelligent group behavior. Not being limited to playing the game of soccer and being completely autonomous, we are also looking at a number of other interesting scenarios. The robots can communicate with each other, e.g. for exchanging positions, information about objects or just the local states they are currently in (e.g. sharing their current objectives with other robots in the group). We are particularly interested in the differences between a behavior-based approach versus a traditional control algorithm at this still very low level of action.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.717-723
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• 2019

Smart systems and services aim to facilitate growing urban populations and their prospects of virtual-real social behaviors, gig economies, factory automation, knowledge-based workforce, integrated societies, modern living, among many more. To satisfy these objectives, smart systems and services must comprises of a complex set of features such as security, ease of use and user friendliness, manageability, scalability, adaptivity, intelligent behavior, and personalization. Recently, artificial intelligence (AI) is realized as a data-driven technology to provide an efficient knowledge representation, semantic modeling, and can support a cognitive behavior aspect of the system. In this paper, an integration of AI with the smart systems and services is presented to mitigate the existing challenges. Several novel researches work in terms of frameworks, architectures, paradigms, and algorithms are discussed to provide possible solutions against the existing challenges in the AI-based smart systems and services. Such novel research works involve efficient shape image retrieval, speech signal processing, dynamic thermal rating, advanced persistent threat tactics, user authentication, and so on.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.607-612
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• 2002

An automatic design method of behaviors in behavior-based robotics is proposed. With this method, a robot can design its behaviors by itself without aids of human designer. Automating design procedure of behaviors can make the human designer free from somewhat tedious endeavor that requires to predict all possible situations in which the robot will work and to design a suitable behavior for each situation. A simple reinforcement learning strategy is the main frame of this method and the key parameter of the learning process is significant change of reward value. A successful application to mobile robot navigation is reported too.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.127-130
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• 1998

In this paper, we propose a method of cooperative control(T-cell modeling) and selection of group behavior strategy(B-cell modeling) based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For the purpose of applying immune system to DARS, a robot is regarded as a B cell, each environmental condition as an antigen, a behavior strategy as an antibody and control parameter as a T-call respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is stimulated and suppressed by other robot using communication. Finally much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based of clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy. By T-cell modeling, adaptation ability of robot is enhanced in dynamic environments.

• Journal of Information Processing Systems
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• v.7 no.4
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• pp.707-716
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• 2011

It is important that desktop grids should be able to aggressively deal with the dynamic properties that arise from the volatility and heterogeneity of resources. Therefore, it is required that task scheduling be able to positively consider the execution behavior that is characterized by an individual resource. In this paper, we implement a log analysis system with REST web services, which can analyze the execution behavior by utilizing the actual log data of desktop grid systems. To verify the log analysis system, we conducted simulations and showed that the resource group-based task scheduling, based on the analysis of the execution behavior, offers a faster turnaround time than the existing one even if few resources are used.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2004.05a
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• pp.186-189
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• 2004

Although magnesium has high potential for structural material due to the lightweight and high specific strength, the structural application has been limited by the low ductility at room temperature. The reason of the poor ductility is few activated slip systems of magnesium (HCP structure) during deformation. As temperature increases, however, additional non-basal slip systems are incorporated to exhibit higher ductility comparable to aluminum. In the present study, a series of tensile tests of Mg-Al alloy has been carried out to study deformation behavior with temperature variation. Analysis of load relaxation test results based on internal variable approach gave information about relationship between the micromechanical character and corresponding deformation behavior of magnesium. Especially, the material parameter, p representing dislocation permeability through barriers was altered from 0.1 to 0.15 as the non-basal slip systems were activated at high temperature.

• Transactions of Materials Processing
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• v.13 no.6 s.70
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• pp.535-539
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• 2004

Although magnesium has high potential for structural material due to the lightweight and high specific strength, the structural application has been limited by the low ductility at room temperature. The reason of the poor ductility is few activated slip systems of magnesium (HCP structure) during deformation. As temperature increases, however, additional non-basal slip systems are incorporated to exhibit higher ductility comparable to aluminum. In the present study, a series of tensile tests of Mg-Al alloy has been carried out to study deformation behavior with temperature variation. Analysis of load relaxation test results based on internal variable approach gave information about relationship between the micromechanical character and corresponding deformation behavior of magnesium. Especially, the material parameter, p representing dislocation permeability through barriers was altered from 0.1 to 0.15 as the non-basal slip systems were activated at high temperature.

• Journal of KIISE
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• v.41 no.12
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• pp.1035-1049
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• 2014

This paper presents a new method to detect attack patterns in security-critical systems, based on a new notion of Behavior Ontology. Generally security-critical systems are large and complex, and they are subject to be attacked in every possible way. Therefore it is very complicated to detect various attacks through a semantic structure designed to detect such attacks. This paper handles the complication with Behavior Ontology, where patterns of attacks in the systems are defined as a sequences of actions on the class ontology of the systems. We define the patterns of attacks as sequences of actions, and the attack patterns can then be abstracted in a hierarchical order, forming a lattice, based on the inclusion relations. Once the behavior ontology for the attack patterns is defined, the attacks in the target systems can be detected both semantically and hierarchically in the ontology structure. When compared to other attack models, the behavior ontology analysis proposed in this paper is found to be very effective and efficient in terms of time and space.