• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.39-47
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• 2009

Recently, the threat of DDoS attacks is increasing and many companies are planned to deploy the DDoS defense solutions in their networks. The DDoS attack usually transmits heavy traffic data to networks or servers and they cannot handle the normal service requests because of running out of resources. Since it is very hard to prevent the DDoS attack beforehand, the strategic plan is very important. In this work, we have conducted modeling and simulation of the DDoS attack by changing the number of servers and estimated the duration that services are available. In this work, the modeling and simulation is conducted using OPNET Modeler. The simulation result can be used as a parameter of trade-off analysis of DDoS defense cost and the service's value. In addition, we have presented a way of estimating the cost effectiveness in deployment of the DDoS defense system.

• Journal of Korea Port Economic Association
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• v.27 no.2
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• pp.333-354
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• 2011

After the terrorist attack of 9/11 on the USA, the security concern to global trade has been raised. In particular, the USA has actively promoted a series of initiatives and rules such as CSI, 24 hour rule, C-TPAT, and so on in the area of logistics activities, which aimed to better protect the country against the potential terrorist threats. While implementing such schemes called as a multi-layed logistics security strategy, a large number of countries trading with USA are facing with the issues of additional time and costs for inspecting cargos in their logistics facilities. As a result, most countries all over the world have sought a way to minimize the impacts from such strategy. The Korea also is preparing the several security programs operated by various ministries, which are aiming to not only improve the efficiency of trade flows but also to ensure supply chain security. However, many companies are expressing the inefficiency of operating such programs. Thus, this paper analyzed several global supply chain security programs currently adopted by international organizations(ISO, WCO, and IMO) and major countries(USA, EU, and Singapore) and suggested a guideline for developing the national logistics security system.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.1-13
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• 2022

As the information and communication environment develops, the environment of military facilities is also development remarkably. In proportion to this, cyber threats are also increasing, and in particular, APT attacks, which are difficult to prevent with existing signature-based cyber defense systems, are frequently targeting military and national infrastructure. It is important to identify attack groups for appropriate response, but it is very difficult to identify them due to the nature of cyber attacks conducted in secret using methods such as anti-forensics. In the past, after an attack was detected, a security expert had to perform high-level analysis for a long time based on the large amount of evidence collected to get a clue about the attack group. To solve this problem, in this paper, we proposed an automation technique that can classify an attack group within a short time after detection. In case of APT attacks, compared to general cyber attacks, the number of attacks is small, there is not much known data, and it is designed to bypass signature-based cyber defense techniques. As an attack model, we used MITRE ATT&CK® which modeled many parts of cyber attacks. We design an impact score considering the versatility of the attack techniques and proposed a group similarity score based on this. Experimental results show that the proposed method classified the attack group with a 72.62% probability based on Top-5 accuracy.

• Korean Security Journal
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• no.10
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• pp.243-272
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• 2005

All measures related to the safety of the casino facilities guarantee safety of facilities that are targets of security guards, protect lives and properties, minimize risks of artificial and natural disaster and crimes. In summary, plan for responding to safety and accidents should be developed not only for the casino facilities but also for the facilities of annexed buildings, and lives and properties of customers and employees. Determine areas in the casino facilities that are prone to accidents and set around-the-clock guard in the areas or maintain surveillance with CCTV and prevent accidents through continuous patrol. These are the most basic and the most important requirements in safety. In addition, casinos which prompt gambling are causing economic and psychological treats to families. To resolve these social issues, casinos have adopted limited entrance system. To support this system, new forms of machine security systems such as video automatic recognition system of fingerprint pattern recognition system should be adopted too. In addition, security guards in casino facilities need to instill themselves with a sense of ownership as well as a strong sense of mission to do the best for customer security and to protect the company assets and employees and manage accidents that could occur without notice. Security guards should do their best to enable manage accidents that could occur without notice. Security guards should do their best to enable tourists who are on the rise due to increase in advanced country-style tourism and leisurely activities to get the utmost satisfaction from the casinos, and as a leader of private security company, establish the foundation for security based on the characteristics of security in Korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.458-465
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• 2020

Technological advances in artificial intelligence are affecting many industries, such as telecommunications, logistics, security, and healthcare, and research and development related to economic, efficiency, linkage with commercial technologies are the current focus. Predicting the changes in the future battlefield environment and ways of conducting war from a strategic point of view, as well as designing/planning the direction of military development for a leading response is not only a basic element to prepare for comprehensive future threats but also an indispensable factor that can produce an optimal effect over a limited budget/time. From this perspective, this study was conducted as part of a technology-driven plan to discover potential future technologies with high potential for use in the defense field and apply them to R&D. In this study, based on research data collected in a defense future technology investigation, the future new technology that requires further research was predicted by considering the redundancy with existing defense research projects and the feasibility of technology. In addition, an empirical study was conducted to verify the significance between the future new defense technology and the evaluation indicators in the AI field.

• Journal of Korean Home Economics Education Association
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• v.32 no.1
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• pp.127-143
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• 2020

The purpose of this study is to develop the clothing safety teaching/learning plan in Home Economics based on the health belief model and to examine the effects of the course using the developed teaching/learning plan on the health belief. Based on ADDIE model, 6 clothing safety teaching/learning plans were developed by applying the health belief model. They consisted of three learning factors of 'harmful substances that can be exposed during the production, wear, wash, and storage of clothes and textile products', 'environment friendly fibers' and 'natural detergents'. Then they were implemented on 7 classes in middle school located in Gyeonggi-do Province from August 20 to September 7 in 2018. The health beliefs data collected before and after the course were analyzed with paired t-test with SPSS/win. As a result, the perceived threat(combination of perceived severity and perceived susceptibility), the perceived benefit, and the self-efficacy were significantly improved. And the perceived barrier was significantly reduced. In conclusion, the home economics clothing safety education course using the health belief model was meaningful as the safety education to enable middle school students to practice safe clothing life from harmful substances. The results of this study are expected to be helpful for activating safety education in home economics.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.5
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• pp.871-883
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• 2014

New types of attacks that mainly compromise the public, portal and financial websites for the purpose of economic profit or national confusion are being emerged and evolved. In addition, in case of 'drive by download' attack, if a host just visits the compromised websites, then the host is infected by a malware. Website falsification detection system is one of the most powerful solutions to cope with such cyber threats that try to attack the websites. Many domestic CERTs including NCSC (National Cyber Security Center) that carry out security monitoring and response service deploy it into the target organizations. However, the existing techniques for the website falsification detection system have practical problems in that their time complexity is high and the detection accuracy is not high. In this paper, we propose website falsification detection system based on image and code analysis for improving the performance of the security monitoring and response service in CERTs. The proposed system focuses on improvement of the accuracy as well as the rapidity in detecting falsification of the target websites.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1191-1200
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• 2022

The COVID-19 pandemic can be deemed one of the greatest hardships faced by mankind in the 21st century. All industries have been severely affected and workers are still experiencing deep difficulties due to the changed working and living environment. Seafarers have been recognized by the international community as key workers since the pandemic began. They are also working internationally to establish a Level Playing Field through the protection of their rights through the Seafarers' Employment Agreement and the implementation of international labour standards. However, despite the obligations under international conventions to be implemented by State parties and the recommendations by international organizations, the rights of seafarers under the Maritime Labour Convention were violated were violated and their occupational safety and health of seafarers were further threatened throughout the pandemic. This article analyzes the impact of the international shipping industry and the implementation of the Maritime Labour Convention based on each country's measures during the COVID-19 pandemic. Furthermore, the amendments of the Maritime Labour Convention adopted through the fourth Special Tripartite Committee were analyzed based on the conference documents and reports to comprehend the implied meaning. The adopted eight amendments to the Maritime Labour Convention are expected to positively affect the seafarers' rights, safety and health in the future, but the international community's efforts should continue because the issues of maximum working hours, maximum service period on board, and the repatriation of seafarers still remain unsettled.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.8
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• pp.355-364
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• 2023

As advanced cyber threats continue to increase in recent years, it is difficult to detect new types of cyber attacks with existing pattern or signature-based intrusion detection method. Therefore, research on anomaly detection methods using data learning-based artificial intelligence technology is increasing. In addition, supervised learning-based anomaly detection methods are difficult to use in real environments because they require sufficient labeled data for learning. Research on an unsupervised learning-based method that learns from normal data and detects an anomaly by finding a pattern in the data itself has been actively conducted. Therefore, this study aims to extract a latent vector that preserves useful sequence information from sequence log data and develop an anomaly detection learning model using the extracted latent vector. Word2Vec was used to create a dense vector representation corresponding to the characteristics of each sequence, and an unsupervised autoencoder was developed to extract latent vectors from sequence data expressed as dense vectors. The developed autoencoder model is a recurrent neural network GRU (Gated Recurrent Unit) based denoising autoencoder suitable for sequence data, a one-dimensional convolutional neural network-based autoencoder to solve the limited short-term memory problem that GRU can have, and an autoencoder combining GRU and one-dimensional convolution was used. The data used in the experiment is time-series-based NGIDS (Next Generation IDS Dataset) data, and as a result of the experiment, an autoencoder that combines GRU and one-dimensional convolution is better than a model using a GRU-based autoencoder or a one-dimensional convolution-based autoencoder. It was efficient in terms of learning time for extracting useful latent patterns from training data, and showed stable performance with smaller fluctuations in anomaly detection performance.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.1
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• pp.19-30
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• 2023

An electric scooter(e-scooter), one popularized micro-mobility vehicle has shown rapidly increasing use in many cities. In South Korea, the use of e-scooters has greatly increased, as some companies have launched e-scooter sharing services in a few large cities, starting with Seoul in 2018. However, the use of e-scooters is still controversial because of issues such as parking and safety. Since the perception toward the means of transportation affects the mode choice, it is necessary to track the trends for electric scooters to make the use of e-scooters more active. Hence, this study aimed to analyze the trends related to e-scooters. For this purpose, we analyzed news articles related to e-scooters published from 2014 to 2020 using dynamic topic modeling to extract issues and sentiment analysis to investigate how the degree of positive and negative opinions in news articles had changed. As a result of topic modeling, it was possible to extract three different topics related to micro-mobility technologies, shared e-scooter services, and regulations for micro-mobility, and the proportion of the topic for regulations for micro-mobility increased as shared e-scooter services increased in recent years. In addition, the top positive words included quick, enjoyable, and easy, whereas the top negative words included threat, complaint, and ilegal, which implies that people satisfied with the convenience of e-scooter or e-scooter sharing services, but safety and parking issues should be addressed for micro-mobility services to become more active. In conclusion, this study was able to understand how issues and social trends related to e-scooters have changed, and to determine the issues that need to be addressed. Moreover, it is expected that the research framework using dynamic topic modeling and sentiment analysis will be helpful in determining social trends on various areas.