• Journal of the Society of Disaster Information
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• v.9 no.3
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• pp.290-299
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• 2013

This study is to present an improvement of security for the National Assembly by survey of persons who use the National Assembly facilities. Most of respondent said that their security consciousness level is above average, and they know National Assembly building is National Major Facility First class but they did not know well what the Major Facility First class is. Many of respondents thought security design of National Assembly building is inadequate, so reinforcement of access control management is necessary. For reinforcement of access control management, security gate and preparing of some obstacles are required. They said that they could put up with inconveniences incurred as a result of reinforcement of access control management, that could be affected positively for the reinforcement. The recognition on the necessity of security education is high, but there is no proper security education program. For practical security education, contents and different method followed by different facilities user should be considered.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.1
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• pp.21-29
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• 2024

With the development of ICT and network, security management of IT infrastructure that has grown in size is becoming very difficult. Many companies and public institutions are having difficulty managing system and network security. In addition, as the complexity of hardware and software grows, it is becoming almost impossible for a person to manage all security. Therefore, AI is essential for network security management. However, since it is very dangerous to operate an attack model in a real network environment, cybersecurity emulation research was conducted through reinforcement learning by implementing a real-life network environment. To this end, this study applied reinforcement learning to the network environment, and as the learning progressed, the agent accurately identified the vulnerability of the network. When a network vulnerability is detected through AI, automated customized response becomes possible.

• Journal of Information Technology Services
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• v.19 no.6
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• pp.83-95
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• 2020

"I think security is only trying to make it uncomfortable." "10% of my work is entering IDs and passwords, such as boot passwords, mobile phone authentication numbers, etc." As reflected in the complaint above, stress caused by information security among organizations' members is increasing. In order to strengthen information security, practical solutions to reduce stress are needed because the motivation of the members is needed in order for organizations to function properly. Therefore, this study attempts to suggest key factors that can enhance security while reducing information security stress among members of organizations. To this end, based on the theory of protection motivation, trust and security stress from information security policies are set as mediating factors to explain changes in security reinforcement behavior. Furthermore, risk, efficacy, and reaction costs of cyberattacks are considered as prerequisites. Our study suggests a solution to the security reinforcement problem by analyzing the factors that influence the behavior of members of organizations. In turn, this can raise protection motivation among members.

• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.112-118
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• 2023

As technology advances, the need for enhanced preparedness against cyber-attacks becomes an increasingly critical problem. Therefore, it is imperative to consider various circumstances and to prepare for cyber-attack strategic technology. This paper proposes a method to solve network security problems by applying reinforcement learning to cyber-security. In general, traditional static cyber-security methods have difficulty effectively responding to modern dynamic attack patterns. To address this, we implement cyber-attack scenarios such as 'Tiny Alpha' and 'Small Alpha' and evaluate the performance of various reinforcement learning methods using Network Attack Simulator, which is a cyber-attack simulation environment based on the gymnasium (formerly Open AI gym) interface. In addition, we experimented with different RL algorithms such as value-based methods (Q-Learning, Deep-Q-Network, and Double Deep-Q-Network) and policy-based methods (Actor-Critic). As a result, we observed that value-based methods with discrete action spaces consistently outperformed policy-based methods with continuous action spaces, demonstrating a performance difference ranging from a minimum of 20.9% to a maximum of 53.2%. This result shows that the scheme not only suggests opportunities for enhancing cybersecurity strategies, but also indicates potential applications in cyber-security education and system validation across a large number of domains such as military, government, and corporate sectors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3104-3123
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• 2022

The development of Vehicular Ad hoc Network (VANET) has greatly improved the efficiency and safety of social transportation, and the routing strategy for VANET has also received high attention from both academia and industry. However, studies on dynamic matching of routing policies with the message types of VANET are in short supply, which affects the operational efficiency and security of VANET to a certain extent. This paper studies the message types in VANET and fully considers the urgency and reliability requirements of message forwarding under various types. Based on the diversified types of messages to be transmitted, and taking the diversified message forwarding strategies suitable for VANET scenarios as behavioral candidates, an adaptive routing method for the VANET message types based on reinforcement learning (RL) is proposed. The key parameters of the method, such as state, action and reward, are reasonably designed. Simulation and analysis show that the proposed method could converge quickly, and the comprehensive performance of the proposed method is obviously better than the comparison methods in terms of timeliness and reliability.

• Journal of Korean Society of societal Security
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• v.1 no.2
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• pp.67-72
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• 2008

To confirm the stability of a cut slope in the road extension construction site, several investigations were carried out and countermeasures of slope was studied. This paper describes a study of design case of extra reinforcement on existing cut slope reinforced by preloading and piles in roads. To investigate the effect of stabilizing piles installed in a cut slope, an instrumentation system also designed, was. As a result that the stabilizing file and earth anchor are considered as the extra reinforcement, both stabilizing pile and earth anchor guarantee the stability of cut slope. However, stabilizing pile is selected in aspects of economy and continuity to the existing cut slop reinforcement including counterweight fill and stabilizing piles.

• Proceedings of KOSOMES biannual meeting
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• 2017.04a
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• pp.105-105
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• 2017

• Convergence Security Journal
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• v.18 no.3
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• pp.3-9
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• 2018

The Deep Deterministic Policy Gradient (DDPG) algorithm is an algorithm that learns by using artificial neural network s and reinforcement learning. Among the studies related to reinforcement learning, which has been recently studied, the D DPG algorithm has an advantage of preventing the cases where the wrong actions are accumulated and affecting the learn ing because it is learned by the off-policy. In this study, we experimented to control the bicycle autonomously by applyin g the DDPG algorithm. Simulation was carried out by setting various environments and it was shown that the method us ed in the experiment works stably on the simulation.

• International Journal of Advanced Culture Technology
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• v.9 no.2
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• pp.106-117
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• 2021

The aim is to find cyber measures in consideration of physical CPTED in order to prepare countermeasures for cybercrime prevention. For this, the six applied principles of CPTED were used as the standard. A new control item was created in connection with the control items of ISO27001. A survey was conducted on former and current investigators and security experts. As a result of the reliability analysis, the Kronbar alpha coefficient value was 0.947, indicating the reliability of the statistical value. As a result of factor analysis, it was reduced to six factors. The following are six factors and countermeasures. Nature monitoring blocks opportunities and strengthens business continuity. Access control is based on management system compliance, personnel security. Reinforcement of territoriality is reinforcement of each wife and ethics. Establishment of security policy to enhance readability, security system maintenance. Increasing usability is seeking ways to utilize, periodic incentives. For maintenance, security education is strength and security-related collective cooperation is conducted. The differentiation of this study was to find countermeasures against cybercrime in the psychological part of the past. However, they approached to find in cyber measures. The limitation of the study is to bring the concept of physical CPTED to the cyber concept.

• Earthquakes and Structures
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• v.7 no.3
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• pp.251-269
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• 2014

To investigate the seismic performance and to obtain quantitative parameters for the requirement of performance-based bridge seismic design approach, 12 reinforced concrete (RC) hollow rectangular bridge column specimens were tested under constant axial load and cyclic bending. Parametric study is carried out on axial load ratio, aspect ratio, longitudinal reinforcement ratio and transverse reinforcement ratio. The damage states of these column specimens were related to engineering limit states to determine the quantitative criteria of performance-based bridge seismic design. The hysteretic behavior of bridge column specimens was simulated based on the fiber model in OpenSees program and the results of the force-displacement hysteretic curves were well agreed with the experimental results. The damage states of residual cracking, cover spalling, and core crushing could be well related to engineering limit states, such as longitudinal tensile strains of reinforcement or compressive strains of concrete, etc. using cumulative probability curves. The ductility coefficient varying from 3.71 to 8.29, and the equivalent viscous damping ratio varying from 0.19 to 0.31 could meet the requirements of seismic design.