• Tunnel and Underground Space
• /
• v.29 no.1
• /
• pp.52-63
• /
• 2019

It is highly in demand to establish a bunker-type underground data center to ensure the safety of national critical data, such as financial information and medical information, and prevent those outflow of national important data. In particular, the security of a data center which is a key national structure has become a social issue due to EMP weapon and earthquakes, but data centers in the nation have not been able to deal with it properly. Therefore, it is necessary to develop an underground data center that is safe from human-induced and natural disasters while reducing power costs by utilizing the benefits of underground spaces such as constant temperature and isolation. In this analysis, the status and trends of data centers around the world were analyzed and based on those trend analyses, the research strategy for underground data center were discussed.

• Journal of the Architectural Institute of Korea Structure & Construction
• /
• v.34 no.2
• /
• pp.57-66
• /
• 2018

When developing projects to build facilities to be shared by both military bases and surrounding communities, strategies are needed to achieve two objectives: 1) minimize missteps and opposition from local communities in the process of developing and implementing such projects, and 2) promote cost-benefit optimization and user-satisfaction. With aim of promoting co-operation and co-existence between military bases and adjust communities, this research proposes esthetical factors to be considered in conceiving civil-military sharing facilities. It seeks experts' opinions on the development of civil-military sharing facilities, and examines critical factors (economic feasibility, security, and satisfaction, etc.) for project development as well as building types suitable for shared-use between military bases and local residents. It then establishes a method to prioritize facility-type and narrow down design factors (considerations and restrictions) in project development by applying quantitative analysis. The methodological approach of the research employs the Delphi survey method to quantitatively analyze qualitative information drawn from experts' opinions. At the first round of the survey, facility types, items for consideration and restrictions are drawn, and then at the second round of the survey, criticality of each item is analyzed. Finally, it reaches a conclusion on suitability of facility types for civil-military sharing facilities, and selects project considerations and restrictions when developing this kind of project.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.10
• /
• pp.1311-1319
• /
• 2019

Currently, the web environment is a commonly used area for sharing information and conducting business. It is becoming an attack point for external hacking targeting on personal information leakage or system failure. Conventional signature-based detection is used in cyber threat but signature-based detection has a limitation that it is difficult to detect the pattern when it is changed like polymorphism. In particular, injection attack is known to the most critical security risks based on web vulnerabilities and various variants are possible at any time. In this paper, we propose a novelty detection technique to detect abnormal state that deviates from the normal state on web-server log dataset(WSLD). The proposed method is a machine learning-based technique to detect a minor anomalous data that tends to be different from a large number of normal data after replacing strings in web-server log dataset with vectors using machine learning-based embedding algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.6
• /
• pp.757-765
• /
• 2021

To carry out multi-domain operations included in the U.S. Department of Defense's national security strategy in 2018, timely data sharing between C4I systems is critical. Several studies of the Korean military have also raised the problems of interface and standardization between C4I systems, and it is necessary to establish a new plan to solve this problem. In this study, a solution to the problem was derived through case analysis that the U.S. Department of Defense has been pursuing for about 20 years to implement the data strategy after establishing the data strategy in 2003. and by establishing a data strategy suitable for the ROK military C4I system operating environment, developing a data model, selecting a standard for data sharing, and proposing a shared data development procedure, we intend to improve the data sharing capability between ROK military C4I systems.

• Journal of radiological science and technology
• /
• v.43 no.6
• /
• pp.481-487
• /
• 2020

Radiation measurement technology has steadily improved and its usage is expanding in various industries such as nuclear medicine, security search, satellite, nondestructive testing, environmental industries and the domain of nuclear power plants (NPPs). Especially, the simultaneous measurements of gamma rays and neutrons can be even more critical for nuclear safety management of spent nuclear fuel and monitoring of the nuclear material. A semiconductor detector comprising cadmium, zinc, and tellurium (CZT) enables to detect gamma-rays due to the significant atomic weight of the elements via immediate neutron and gamma-ray detection. Semiconductor sensors might be used for nuclear safety management by monitoring nuclear materials and spent nuclear fuel with high spatial resolution as well as providing real-time measurements. We aim to introduce a portable nuclide-analysis device that enables the simultaneous measurements of neutrons and gamma rays using a CZT sensor. The detector has a high density and wide energy band gap, and thus exhibits highly sensitive physical characteristics and characteristics are required for performing neutron and gamma-ray detection. Portable nuclide-analysis device is used on NPP-decommissioning sites or the purpose of nuclear nonproliferation, it will rapidly detect the nuclear material and provide radioactive-material information. Eventually, portable nuclide-analysis device can reduce measurement time and economic costs by providing a basis for rational decision making.

• Journal of the Korea Society for Simulation
• /
• v.31 no.2
• /
• pp.11-20
• /
• 2022

There is a critical need for AI assistance in guard operations of Army base perimeters, which is exacerbated by changes in the national defense and security environment such as force reduction. In addition, the possibility for human error inherent to perimeter guard operations attests to the need for an innovative revamp of current systems. The purpose of this study is to propose a real-time object detection AI tailored to military CCTV surveillance with three unique characteristics. First, training data suitable for situations in which relatively small objects must be recognized is used due to the characteristics of military CCTV. Second, we utilize a data augmentation algorithm suited for military context applied in the data preparation step. Third, a noise reduction algorithm is applied to account for military-specific situations, such as camouflaged targets and unfavorable weather conditions. The proposed system has been field-tested in a real-world setting, and its performance has been verified.

• Fisheries and Aquatic Sciences
• /
• v.26 no.4
• /
• pp.268-281
• /
• 2023

Coral reef fisheries are prominent for the archipelagic countries' food sufficiency and security. Studies showed that fish abundance and biomass are affected by biophysical variables. The present study determines which biophysical variables are important predictors of fish diversity, abundance, and biomass. The study used available monitoring data from the Indonesian Research Center for Oceanography, the National Board for Research and Innovation. Data were collected from 245 transects in 19 locations distributed across the Indonesian Archipelago, including the eastern Indian Ocean, Sunda Shelf (Karimata Sea), Wallacea (Flores and Banda Seas), and the western Pacific Ocean. Principal component analysis and multiple regression model were administered to 13 biophysical metrics against 11 variables of coral reef fishes, i.e., diversity, abundance, and biomass of coral reef fishes at three trophic levels. The results showed for the first time that the covers of other fauna, coral rubbles, and soft corals were the three most important predictor variables for nearly all coral reef fish variables. Other fauna cover was the important predictor for all 11 coral reef fish variables. Coral rubble cover was the predictor for ten variables, but carnivore fish abundance. Soft coral cover was a good predictor for corallivore, carnivore, and targeted fishes. Despite important predictors for corallivore and carnivore fish variables, hard coral cover was not the critical predictor for herbivore fish variables. The other important predictor variables with a consistent pattern were dead coral covered with algae and rocks. Dead coral covered with algae was an important predictor for herbivore fishes, while the rock was good for only carnivore fishes.

• Nuclear Engineering and Technology
• /
• v.55 no.6
• /
• pp.2315-2324
• /
• 2023

Space nuclear reactors are becoming popular in deep space exploration owing to their advantages of high-power density and stability. Following the fourth-generation nuclear reactor technology, a conceptual design of the dual drum-controlled space molten salt reactor (D²-SMSR) is proposed. The reactor concept uses molten salt as fuel and heat pipes for cooling. A new reactivity control strategy that combines control drums and safety drums was adopted. Critical physical characteristics such as neutron energy spectrum, neutron flux distribution, power distribution and burnup depth were calculated. Flow and heat transfer characteristics such as natural convection, velocity and temperature distribution of the D²-SMSR under low gravity conditions were analyzed. The reactivity control effect of the dual-drums strategy was evaluated. Results showed that the D²-SMSR with a fast spectrum could operate for 10 years at the full power of 40 kWth. The D²-SMSR has a high heat transfer coefficient between molten salt and heat pipe, which means that the core has a good heat-exchange performance. The new reactivity control strategy can achieve shutdown with one safety drum or three control drums, ensuring high-security standards. The present study can provide a theoretical reference for the design of space nuclear reactors.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.46 no.4
• /
• pp.1-14
• /
• 2023

As markets and industries continue to evolve rapidly, technology opportunity discovery (TOD) has become critical to a firm's survival. From a common consensus that TOD based on a firm's capabilities is a valuable method for small and medium-sized enterprises (SMEs) and reduces the risk of failure in technology development, studies for TOD based on a firm's capabilities have been actively conducted. However, previous studies mainly focused on a firm's technological capabilities and rarely on business capabilities. Since discovered technologies can create market value when utilized in a firm's business, a firm's current business capabilities should be considered in discovering technology opportunities. In this context, this study proposes a TOD method that considers both a firm's business and technological capabilities. To this end, this study uses patent data, which represents the firm's technological capabilities, and trademark data, which represents the firm's business capabilities. The proposed method comprises four steps: 1) Constructing firm technology and business capability matrices using patent classification codes and trademark similarity group codes; 2) Transforming the capability matrices to preference matrices using the fuzzy function; 3) Identifying a target firm's candidate technology opportunities using the collaborative filtering algorithm; 4) Recommending technology opportunities using a portfolio map constructed based on technology similarity and applicability indices. A case study is conducted on a security firm to determine the validity of the proposed method. The proposed method can assist SMEs that face resource constraints in identifying technology opportunities. Further, it can be used by firms that do not possess patents since the proposed method uncovers technology opportunities based on business capabilities.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.2
• /
• pp.456-477
• /
• 2024

With information technology's rapid development, the Internet faces serious security problems. Studies have shown that malware has become a primary means of attacking the Internet. Therefore, adversarial samples have become a vital breakthrough point for studying malware. By studying adversarial samples, we can gain insights into the behavior and characteristics of malware, evaluate the performance of existing detectors in the face of deceptive samples, and help to discover vulnerabilities and improve detection methods for better performance. However, existing adversarial sample generation methods still need help regarding escape effectiveness and mobility. For instance, researchers have attempted to incorporate perturbation methods like Fast Gradient Sign Method (FGSM), Projected Gradient Descent (PGD), and others into adversarial samples to obfuscate detectors. However, these methods are only effective in specific environments and yield limited evasion effectiveness. To solve the above problems, this paper proposes a malware adversarial sample generation method (PixGAN) based on the pixel attention mechanism, which aims to improve adversarial samples' escape effect and mobility. The method transforms malware into grey-scale images and introduces the pixel attention mechanism in the Deep Convolution Generative Adversarial Networks (DCGAN) model to weigh the critical pixels in the grey-scale map, which improves the modeling ability of the generator and discriminator, thus enhancing the escape effect and mobility of the adversarial samples. The escape rate (ASR) is used as an evaluation index of the quality of the adversarial samples. The experimental results show that the adversarial samples generated by PixGAN achieve escape rates of 97%, 94%, 35%, 39%, and 43% on the Random Forest (RF), Support Vector Machine (SVM), Convolutional Neural Network (CNN), Convolutional Neural Network and Recurrent Neural Network (CNN_RNN), and Convolutional Neural Network and Long Short Term Memory (CNN_LSTM) algorithmic detectors, respectively.