• Journal of Advanced Navigation Technology
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• v.25 no.4
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• pp.305-312
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• 2021

Even though various types of sensors are being used for security applications, radar sensors are being suggested as an alternative due to the privacy issues. Among those radar sensors, PD radar has high-complexity receiver, but, FMCW radar requires fewer resources. However, FMCW has disadvantage from the use of 2D-FFT which increases the complexity, and it is difficult to distinguish people from objects those are stationary. In this paper, we present the design and the implementation results of the radar signal processor (RSP) that can distinguish between people and object by respiration measurement using phase estimation without 2D-FFT. The proposed RSP is designed with Verilog-HDL and is implemented on FPGA device. It was confirmed that the proposed RSP includes 6,425 LUT, 4,243 register, and 12,288 memory bits with 92.1% accuracy for target's breathing status.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.377-388
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• 2022

Metaverse, realistic virtual space technology has become a hot topic. However, due to the lack of an institutional system to the metaverse environment, concerns are rising over the leakage of industrial confidentiality, including digital assets produced, stored, processed, and transferred within the metaverse. Digital forensics, a technology to defend against hacking attacks in cyberspace, cannot be used in metaverse space, and there is no basis for calculating the extent of damage and tracking responsibility, making it difficult to respond to human resources leakage and cyberhacking effectively. In this paper, we define the scope of industrial confidentiality information and leakage scenario and propose policy and institutional measures based on problems in each metaverse scenario. As a result of the study, it was necessary to prepare a standardized law on Extra-territorial search and seizure issues and a system for collecting cryptocurrency evidence to respond to industrial confidentiality leaks in the metaverse. The study expects to contribute to industrial technology development by preparing in advance for problems that may arise in metaverse technology.

• Analyses & Alternatives
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• v.4 no.1
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• pp.63-87
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• 2020

This article not only theoretically explores the necessity and effect of constructive minilateralism and subregionalism in Northeast Asia, but also delves into a series of practical solutions from viewpoint of seeking common ground while reserving differences in this region. The main contents are as follows: First, the various obstacles that hinder the formation of regionalism, subregionalism and minilateralism in the Northeast Asia are discussed. That is to say, geopolitical realism, My Country First ideology, exclusive nationalism in the socio-historical context, and North Korea's latest provocations, etc. Second, this article explores the philosophy and basic principles of realizing Northeast Asia regionalism and minilateralism. Third, in the 21st century, Northeast Asia becomes the center of the world. It examines the core points, controversial focus and platform for building sub regionalism in the region. Finally, based on the institutional platform such as minilateralism and sub regionalism, the various ideas and practical plans of cross-border cooperation among major countries in Northeast Asia were discussed. Because there are a lot of obstacles, so first of all it is more appropriate to promote economic or functional minilateralism or sub regionalism than multilateral cooperation. In order to promote the formation of regionalism and minilateralism in Northeast Asia, the issues to be considered are as follows: First, for the sake of leading regional solidarity and minilateral economic cooperation, it is advisable for China, as a regional economic power, to implement a stable and responsible diplomacy. Secondly, regional solidarity based on credible politics and security should be promoted for a long time beyond the level of economic cooperation. Third, the primary prerequisite for the realization of Northeast Asian regionalism is that in the process of denuclearization of North Korea, the stability and peace mechanism of the Korean Peninsula should be established. Fourth, with the continued hegemonic competition between the United States and China in Northeast Asia, under the circumstance that countries in the region are pushed into so-called "East Asian Paradox", it is profoundly important for them to consider transition from the hostile relationship as the "Thucydides trap" to the order of "coexistence" in which competition and cooperation run side by side, and the two countries should explore a conversion plan for the foreign policy line. This mutual cooperation and peaceful coexistence of the US-China relationship will create a friendly atmosphere for the formation of regionalism in Northeast Asia. In the future, the cooperation of minilateralism in Northeast Asia will break the existing conflict between the maritime forces and the continental forces in order to promote peace. And along with the philosophy that "peace is economy", recent policies of common prosperity as the framework, such as China's "Belt and Road Initiative", North Korea's "Special Zone and Development Zone Policy", Russia's "New Eastern Policy", Japan's participation in the Belt and Road Initiative and South Korea's The "Korean Peninsula New Economy Map" are organically linked and it should promote the so-called "networked regionalism".

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.81-88
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• 2022

This study is to investigate the perception of domestic appraisers about the possibility of using artificial intelligence (AI) and related risks from the use of AI in the appraisal industry. We conducted a mobile survey of evaluators from February 10 to 18, 2022. We collected survey data from 193 respondents. Frequency analysis and multiple response analysis were performed for basic analysis. When AI is used in the appraisal industry, factor analysis was used to analyze various types of risks. Although appraisers have a positive perception of AI introduction in the appraisal industry, they considered collateral, consulting, and taxation, mainly in areas where AI is likely to be used and replaced, mainly negative effects related to job losses and job replacement. They were more aware of the alternative risks caused by AI in the field of human labor. I was very aware of responsibilities, privacy and security, and the risk of technical errors. However, fairness, transparency, and reliability risks were generally perceived as low risk issues. Existing studies have mainly studied analysis methods that apply AI to mass evaluation models, but this study focused on the use and risk of AI. Understanding industry experts' perceptions of AI utilization will help minimize potential risks when AI is introduced on a large scale.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.30-37
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• 2021

Various devices are connected to the Internet, and attacks using the Internet are occurring. Among such attacks, there are attacks that use malicious URLs to make users access to wrong phishing sites or distribute malicious viruses. Therefore, how to detect such malicious URL attacks is one of the important security issues. Among recent deep learning technologies, neural networks are showing good performance in image recognition, speech recognition, and pattern recognition. This neural network can be applied to research that analyzes and detects patterns of malicious URL characteristics. In this paper, performance analysis according to various parameters was performed on a method of detecting malicious URLs using neural networks. In this paper, malicious URL detection performance was analyzed while changing the activation function, learning rate, and neural network structure. The experimental data was crawled by Alexa top 1 million and Whois to build the data, and the machine learning library used TensorFlow. As a result of the experiment, when the number of layers is 4, the learning rate is 0.005, and the number of nodes in each layer is 100, the accuracy of 97.8% and the f1 score of 92.94% are obtained.

• Applied Chemistry for Engineering
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• v.33 no.2
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• pp.126-132
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• 2022

Alkaline fuel cells using liquid fuels such as hydrazine and ammonia are gaining great attention as a clean and renewable energy solution possibly owing to advantages such as excellent energy density, simple structure, compact size in fuel container, and ease of storage and transportation. However, common shortcomings including cathode flooding, fuel crossover, side yield reactions, and fuel security and toxicity are still challenging issues. Real time monitoring of fuel concentrations integrated into a fuel cell device can help improving fuel cell performance via predicting any loss of fuels used at a cathode for efficient energy production. There have been extensive research efforts made on developing real-time sensing platforms for hydrazine and ammonia. Among these, recent advancements in electrochemical sensors offering high sensitivity and selectivity, easy fabrication, and fast monitoring capability for analysis of hydrazine and ammonia concentrations will be introduced. In particular, research trend on the integration of metallic and metal oxide nanoparticles and also their hybrids with carbon-based nanomaterials into electrochemical sensing platforms for improvement in sensitivity and selectivity will be highlighted.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.39-48
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• 2022

Cyberattacks around the world continue to increase, and their damage extends beyond government facilities and affects civilians. These issues emphasized the importance of developing a system that can identify and detect cyber anomalies early. As above, in order to effectively identify cyber anomalies, several studies have been conducted to learn BGP (Border Gateway Protocol) data through a machine learning model and identify them as anomalies. However, BGP data is unbalanced data in which abnormal data is less than normal data. This causes the model to have a learning biased result, reducing the reliability of the result. In addition, there is a limit in that security personnel cannot recognize the cyber situation as a typical result of machine learning in an actual cyber situation. Therefore, in this paper, we investigate BGP (Border Gateway Protocol) that keeps network records around the world and solve the problem of unbalanced data by using SMOTE. After that, assuming a cyber range situation, an autoencoder classifies cyber anomalies and visualizes the classified data. By learning the pattern of normal data, the performance of classifying abnormal data with 92.4% accuracy was derived, and the auxiliary index also showed 90% performance, ensuring reliability of the results. In addition, it is expected to be able to effectively defend against cyber attacks because it is possible to effectively recognize the situation by visualizing the congested cyber space.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.151-159
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• 2010

Currently, by using the Internet, We can do varius things such as Web surfing, email, on-line shopping, stock trading on your home or office. However, as being out of the concept of security from the beginning, it is the big social issues that malicious user intrudes into the system through the network, on purpose to steal personal information or to paralyze system. In addition, network intrusion by ordinary people using network attack tools is bringing about big worries, so that the need for effective and powerful intrusion detection system becomes very important issue in our Internet environment. However, it is very difficult to prevent this attack perfectly. In this paper we proposed the algorithm for the detection of DoS attacks, and developed attack detection tools. Through learning in a normal state on Step 1, we calculate thresholds, the number of packets that are coming to each port, the median and the average utilization of each port on Step 2. And we propose values to determine how to attack detection on Step 3. By programing proposed attack detection algorithm and by testing the results, we can see that the difference between the median of packet mounts for unit interval and the average utilization of each port number is effective in detecting attacks. Also, without the need to look into the network data, we can easily be implemented by only using the number of packets to detect attacks.

• The Korean Society of Law and Medicine
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• v.24 no.1
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• pp.67-98
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• 2023

In the early stages of the COVID-19 pandemic, Korea took the lead in implementing "social distancing" policies more strongly than other countries. In addition to making it mandatory to wear a mask according to the policy, all patients using medical institutions are tested for COVID-19 to prevent Healthcare-Associated Infections, and only those patients who test negative have been regulated to receive face-to-face medical treatment. In this process, situations such as the disabled, who have difficulty wearing masks, were not taken into account, and emergency patients did not receive timely treatment or surgery from medical personnel. In response, the National Human Rights Commission of Korea has decided that forcing everyone to wear a mask and restricting access to medical institutions constitutes discrimination against the disabled. Therefore, the purposes this study has that, the first is to review cases of human rights discrimination against persons with disabilities due to measures to prevent the transmission of infectious diseases that did not consider the characteristics of persons with disabilities in the COVID-19 situation and issues regarding the decisions of the National Human Rights Commission of Korea, the second is to find a reasonable plan and the need for measures to prevent refusal of treatment by medical institutions for the disabled who have difficulty wearing masks.

• International Area Studies Review
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• v.15 no.1
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• pp.87-106
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• 2011

Using an event study, this paper investigates stock price reactions on Korean listed firms' convertible bond (CB) issue announcements over the sample period of January 2000 to November 2007. This study finds that on the Korean Security market, the CB issue announcements are associated with an increase in shareholder wealth on the announcement date. An information leakage by insider traders is also observable at preannouncement dates. Unlike the prior studies that indicate a prevailing negative effect on the announcements, this paper shows that domestic CB issue announcements as well as offshore ones yield a positive impact on the stock prices. This presents that in terms of stock price reactions to the CB issue announcements, the two CB issue markets show the positively same effects on shareholder wealth for the post-2000 period. For its drivers, this paper suggests that on the Korean market, firm size have negative relationship with the increase in the wealth incurred by the announcements. By contrast, an issue to maturity, a growth opportunity, and a relative issue size make a positive impact on it.