• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.spc
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• pp.23-29
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• 2022

To detect harmful chemical substances in seawater, we fabricated a prototype sensor and evaluated its performance. The prototype sensor consisted of a detector, housing, and driving circuit. We built the detector by printing an Indium-Tin-Oxide (ITO) nanoparticle film on a flexible substrate, and it had two detection parts for simultaneous detection of temperature and HNS concentration. The housing connected the detector and the driving circuit and was made of Teflon material to prevent chemical reactions that may affect sensor performance. The driving circuit supplied electric power, and display measured data using a bridge circuit and an Arduino board. We evaluated the sensor performances such as response (ΔR), the limit of detection (LOD), response time, and errors to confirm the specification.

• 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 the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.194-199
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• 2022

Preprocessing for high-quality data is required for high accuracy and usability in various and complex image data-based industries. However, when a contaminated hostile example that combines noise with existing image or video data is introduced, which can pose a great risk to the company, it is necessary to restore the previous damage to ensure the company's reliability, security, and complete results. As a countermeasure for this, restoration was previously performed using Defense-GAN, but there were disadvantages such as long learning time and low quality of the restoration. In order to improve this, this paper proposes a method using adversarial examples created through FGSM according to image segmentation in addition to using the VQ-VAE model. First, the generated examples are classified as a general classifier. Next, the unsegmented data is put into the pre-trained VQ-VAE model, restored, and then classified with a classifier. Finally, the data divided into quadrants is put into the 4-split-VQ-VAE model, the reconstructed fragments are combined, and then put into the classifier. Finally, after comparing the restored results and accuracy, the performance is analyzed according to the order of combining the two models according to whether or not they are split.

• Informatization Policy
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• v.30 no.1
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• pp.41-66
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• 2023

This study aims to reveal the direction of municipal ordinances for smart cities, while focusing on 74 municipal ordinances from 72 municipal governments through topic modeling. As a result, the main keywords that show a high frequency belong to establishment and operations of the Smart City Committee. From the result of topic modeling Latent Dirichlet Allocation(LDA), it classifies municipal ordinances for smart cities into eight topics as follows: Topic 1(security for process of smart cities), Topic 2(promotion of smart city industry), Topic 3(composition of a smart city consultative body for local residents), Topic 4(support system for smart cities), Topic 5(management for personal information), Topic 6(use of smart city data), Topic 7(implementation for intelligent public administration), and Topic 8(smart city promotion). As for topic categorization by region, Topics 5, 6, and 8 which are mostly related to the practical operation of smart cities have a significant portion of municipal ordinances for smart cities in the Seoul metropolitan area. Then, Topics 2, 3, and 4 which are mostly related to the initial implementation of smart cities have a significant portion of municipal ordinances for smart cities in provincial areas.

• Korean Journal of Environmental Biology
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• v.41 no.1
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• pp.41-53
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• 2023

E171, a mixture of titanium dioxide, has been widely used as a food additive due to its whitening effect and low toxicity. However, it has been proven that E171 is no longer safe for public health. So far, there are insufficient studies on the toxic effects of E171 on organisms especially using standardized test methods. In this study, toxicity assessments of E171 to two aquatic species, water flea (Daphnia magna) and zebrafish (Danio rerio), were performed using modified standardized test methods based on the physicochemical properties of E171. The hydrodynamic diameter, polydispersity index, and turbiscan stability index (TSI) were measured to ensure the dispersion stability of E171 in exposure media during the test period. The EC₅₀ for immobilization of water flea was 141.7 mg L^-1 while zebrafish was not affected until 100 mg L^-1 of E171. Measurements of reactive oxygen species (ROS) and antioxidant enzyme activities confirmed that E171 induced oxidative stress, leading to the activation of superoxide dismutase and catalase in both water flea and zebrafish, although the expression of antioxidant enzyme genes differed between species. These results suggested the potential risk of E171 to aquatic organisms and provided toxicological insights into the impacts of E171 on the environment.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.67-76
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• 2023

Although deep learning models are making innovative achievements in the field of computer vision, the problem of vulnerability to adversarial examples continues to be raised. Adversarial examples are attack methods that inject fine noise into images to induce misclassification, which can pose a serious threat to the application of deep learning models in the real world. In this paper, we propose a model that detects adversarial examples using differences in predictive values between edge-learned classification models and underlying classification models. The simple process of extracting the edges of the objects and reflecting them in learning can increase the robustness of the classification model, and economical and efficient detection is possible by detecting adversarial examples through differences in predictions between models. In our experiments, the general model showed accuracy of {49.9%, 29.84%, 18.46%, 4.95%, 3.36%} for adversarial examples (eps={0.02, 0.05, 0.1, 0.2, 0.3}), whereas the Canny edge model showed accuracy of {82.58%, 65.96%, 46.71%, 24.94%, 13.41%} and other edge models showed a similar level of accuracy also, indicating that the edge model was more robust against adversarial examples. In addition, adversarial example detection using differences in predictions between models revealed detection rates of {85.47%, 84.64%, 91.44%, 95.47%, and 87.61%} for each epsilon-specific adversarial example. It is expected that this study will contribute to improving the reliability of deep learning models in related research and application industries such as medical, autonomous driving, security, and national defense.

• Journal of Korean Society of Disaster and Security
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• v.16 no.2
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• pp.1-13
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• 2023

As interest in urban safety has increased since COVID-19, various institutions have developed and used indicators that evaluate the safety city model. Yongsan-gu was ranked No. 1 in 2021 by Social Safety Index evaluation and was selected as the safest city in Korea. However, the Itaewon disaster in Yongsan-gu in 2022 caused many casualties. The study of indicators for evaluating cities' safety was necessary. This study aims to examine domestic and foreign safe city models and review the differences between each model and the indicators used to evaluate safe cities. As a result of collecting 11 safe city models and analyzing each evaluation index, safe city models can be classified into program-based safe city models, such as the World Health Organization's International safe community and the UN Office for Disaster Risk Reduction's International Safe city. Considering the diversification of threats to safety, it is reasonable to comprehensively consider digital security, health safety, infrastructure safety, personal safety, environmental safety, traffic safety, fire safety, crime safety, life safety, suicide, and infectious diseases when evaluating safe cities as evaluation parameters.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.11a
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• pp.116-118
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• 2023

In recent years, the need for economical and sustainable ship routing has emerged due to the enforced regulations on environmental issues. Despite the development of weather forecasting technology, maritime accidents by rough waves have continued to occur due to incorrect weather forecasts. In this study, onboard measurements are conducted to observe the acutal situation on merchant ships in operation encountering rough waves. The types of measured data include information related to navigation (Ship's position, speed, bearing, rudder angle) and engine (engine revolutions, power, shaft thrust, fuel consumption), weather conditions (wind, waves), and ship motions (roll, pitch, and yaw). These ship experiments was conducted to 28,000 DWT bulk carrier, 63,000 DWT bulk carrier, 20,000 TEU container ship, and 12,000 TEU container ship. The actual ship experiment of each ship is intended to acquire various types of data and utilize them for multi-objective studies related to ship operation. Additionally, in order to confirm the sea conditions, the directional wave spectrum was reproduced using a wave simulation model. Through data collection from ship experiments and wave simulations, various studies could be proceeding such as the measurement for accurate wave information by marine radar and analysis for cargo collapse accidents. In addition, it is expected to be utilized in various themes from the perspective of safety and efficiency in ship operation.

• Journal of Industrial Convergence
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• v.22 no.6
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• pp.51-59
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• 2024

The purpose of the paper is to suggest government policies that are practically helpful to small business owners in pandemic situations such as COVID-19. To this end, keyword frequency analysis and word cloud analysis of text mining analysis were performed by crawling news articles centered on the keywords "COVID-19 Support for Small Businesses", "The Impact of Small Businesses by Response System to COVID-19 Infectious Diseases", and "COVID-19 Small Business Economic Policy", and major issues were identified through LDA topic modeling analysis. As a result of conducting LDA topic modeling, the support policy for small business owners formed a topic label with government cash and financial support, and the impact of small business owners according to the COVID-19 infectious disease response system formed a topic label with a government-led quarantine system and an individual-led quarantine system, and the COVID-19 economic policy formed a topic label with a policy for small business owners to acquire economic crisis and self-sustainability. Focusing on the organized topic label, it was intended to provide basic data for small business owners to understand the damage reduction policy for small business owners and the policy for enhancing market competitiveness in the future pandemic situation.

• The Transactions of the Korea Information Processing Society
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• v.13 no.2
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• pp.34-40
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• 2024

Secret sharing is a cryptographic technique that involves dividing a secret or a piece of sensitive information into multiple shares or parts, which can significantly increase the confidentiality of a secret. There has been a lot of research on secret sharing for different contexts or situations. Tassa's conjunctive secret sharing method employs polynomial derivatives to facilitate hierarchical secret sharing. However, the use of derivatives introduces several limitations in hierarchical secret sharing. Firstly, only a single group of participants can be created at each level due to the shares being generated from a sole derivative. Secondly, the method can only reconstruct a secret through conjunction, thereby restricting the specification of arbitrary secret reconstruction conditions. Thirdly, Birkhoff interpolation is required, adding complexity compared to the more accessible Lagrange interpolation used in polynomial-based secret sharing. This paper introduces the multi-compartment secret sharing method as a generalization of the conjunctive hierarchical secret sharing. Our proposed method first encrypts a secret using external groups' shares and then generates internal shares for each group by embedding the encrypted secret value in a polynomial. While the polynomial can be reconstructed with the internal shares, the polynomial just provides the encrypted secret, requiring external shares for decryption. This approach enables the creation of multiple participant groups at a single level. It supports the implementation of arbitrary secret reconstruction conditions, as well as conjunction. Furthermore, the use of polynomials allows the application of Lagrange interpolation.