• Journal of the Korean Society of Safety
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• v.37 no.5
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• pp.80-88
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• 2022

The Korean nuclear industry had developed the SPACE (Safety and Performance Analysis Code for nuclear power plants) code, which adopts a two-fluid, three-field model that is comprised of gas, continuous liquid and droplet fields and has the capability to simulate three-dimensional models. According to the revised law by the Nuclear Safety and Security Commission (NSSC) in Korea, the multiple failure accidents that must be considered for the accident management plan of a nuclear power plant was determined based on the lessons learned from the Fukushima accident. Generally, to improve the reliability of the calculation results of a safety analysis code, verification is required for the separate and integral effect experiments. Therefore, the goal of this work is to verify the calculation capability of the SPACE code for multiple failure accidents. For this purpose, an experiment was conducted to simulate a Control Element Drive Mechanism (CEDM) break with a safety injection failure using the ATLAS test facility, which is operated by Korea Atomic Energy Research Institute (KAERI). This experiment focused on the comparison between the experiment results and code calculation results to verify the performance of the SPACE code. The results of the overall system transient response using the SPACE code showed similar trends with the experimental results for parameters such as the system pressure, mass flow rate, and collapsed water level in component. In conclusion, it can be concluded that the SPACE code has sufficient capability to simulate a CEDM break with a safety injection failure accident.

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

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.562-574
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• 2012

Simulation validation techniques which have been employed in most studies are statistical analysis, which validate a model with mean or variance of throughput and resource utilization as an evaluation object. However, these methods have not been able to ensure the reliability of individual elements of the model well. To overcome the problem, the weighted F-measure method was proposed, but this technique also had some limitations. First, it is difficult to apply the technique to complex system environment with numerous values of interarrival time because it assigns a class to an individual value of interarrival time. In addition, due to unbounded weights, the value of weighted F-measure has no lower bound, so it is difficult to determine its threshold. Therefore, this paper propose weighted F-measure technique with cluster analysis to solve these problems. The classes for the technique are defined by each cluster, which reduces considerable number of classes and enables to apply the technique to various systems. Moreover, we improved the validation technique in the way of assigning minimum bounded weights without any lack of objectivity.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.29-39
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• 2021

As damages to individuals, private sectors, and businesses increase due to newly occurring cyber attacks, the underlying network security problem has emerged as a major problem in computer systems. Therefore, NIDS using machine learning and deep learning is being studied to improve the limitations that occur in the existing Network Intrusion Detection System. In this study, a deep learning-based NIDS model study is conducted using the Convolution Neural Network (CNN) algorithm. For the image classification-based CNN algorithm learning, a discrete algorithm for continuity variables was added in the preprocessing stage used previously, and the predicted variables were expressed in a linear relationship and converted into easy-to-interpret data. Finally, the network packet processed through the above process is mapped to a square matrix structure and converted into a pixel image. For the performance evaluation of the proposed model, NSL-KDD, a representative network packet data, was used, and accuracy, precision, recall, and f1-score were used as performance indicators. As a result of the experiment, the proposed model showed the highest performance with an accuracy of 85%, and the harmonic mean (F1-Score) of the R2L class with a small number of training samples was 71%, showing very good performance compared to other models.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.570-578
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• 2019

In this era of big data, a variety of government organizations are trying to create new added value via Information Integration. Therefore, several projects related to government agencies' information sharing have activated system connection/integration. The risk factors of system operation, however, have increased as the volume of Information Integration System grows. The interference in information sharing is predicted to affect the operation of the agencies, and the issue will grow even worse with massive impact on civil society when the agency operation is interrupted due to system failures in terms of infrastructure, software, data quality, and security. Diverse studies related to the maintenance of Information System have been conducted, but there is currently no evaluation framework for the operational system of Information Integration between various government agencies. In this respect, this study distinguishes each of the Information System components, Data, IT, People, Process, systematizes with Plan-Do-See, and finally presents a maturity model for Information Integration. Nine derived processes were analyzed through interview and questionnaires from Information Integration System officials, further suggesting maturity stage applying CMMI. This model allows diagnosis of the maturity level of an Information Integration System, and is expected to be utilized as resource for improving organizational processes.

• The Korean Journal of Archival Studies
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• no.25
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• pp.3-46
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• 2010

Digital records management is one whole system in which many social and technical elements are interacting. To maintain the trustworthiness, the repository needs periodical audit and certification. Thus, individual electronic records management agency needs toolkit that can be used to self-evaluate their trustworthiness continuously, and self-assess their atmosphere and system to recognize deficiencies. The purpose of this study is development of self-certification toolkit for repositories, which synthesized and analysed such four international standard and best practices as OAIS Reference Model(ISO 14721), TRAC, DRAMBORA, and the assessment report conducted and published by TNA/UKDA, as well as MoRe2 and current national laws and standards. As this paper describes and demonstrate the development process and the framework of this self-certification toolkit, other electronic records management agencies could follow the process and develop their own toolkit reflecting their situation, and utilize the self-assessment results in-house. As a result of this research, 12 areas for assessment were set, which include (organizational) operation management, classification system and master data management, acquisition, registration and description, storage and preservation, disposal, services, providing finding aids, system management, access control and security, monitoring/audit trail/statistics, and risk management. In each 12 area, the process map or functional charts were drawn and business functions were analyzed, and 54 'evaluation criteria', consisted of main business functional unit in each area were drawn. Under each 'evaluation criteria', 208 'specific evaluation criteria', which supposed to be implementable, measurable, and provable for self-evaluation in each area, were drawn. The audit and certification toolkit developed by this research could be used by digital repositories to conduct periodical self-assessment of the organization, which would be used to supplement any found deficiencies and be used to reflect the organizational development strategy.

• Journal of the Society of Disaster Information
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• v.17 no.2
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• pp.289-305
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• 2021

Purpose: The purpose of this study is to check the importance of higher level, sub higher level and lower alternative factor and the factor for relieved life and also check the comprehensive priority in executed "Safety and relieved life level improvement of apartment house residents by AHP analysis". Method: The safety management evaluation elements and alternatives have been arranged as hierarchical structure based on the preceding studies and the advice of experts for the maintenance and system of apartment house in this study. Study model is used for the survey of pair wise comparison composition targeting experts and AHP analysis method is used for alternative plan ranking, etc. Result: The response result of survey secured the consistency and it is confirmed that safety inspection for apartment house electricity facility is most important for higher level, safety inspection, detailed inspection and diagnosis evaluation are most important for sub higher level and plumbing equipments is most important for alternatives based on the analysis result of relative weight comparison for sub higher level and alternatives for final goal attainment of the study. Conclusion: Plumbing equipments, crime prevention safety and electrical safety are shown as top priority alternatives when observe it with expert manager's point of view for apartment house. It shows that securing the importance of living safety accident and deciding the level of relieved life can be improved are the alternatives of pre-prevention and management strengthening.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.3
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• pp.91-98
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• 2021

Today's information and communication technology is rapidly developing, the security of IT infrastructure is becoming more important, and at the same time, cyber attacks of various forms are becoming more advanced and sophisticated like intelligent persistent attacks (Advanced Persistent Threat). Early defense or prediction of increasingly sophisticated cyber attacks is extremely important, and in many cases, the analysis of network-based intrusion detection systems (NIDS) related data alone cannot prevent rapidly changing cyber attacks. Therefore, we are currently using data generated by intrusion detection systems to protect against cyber attacks described above through Host-based Intrusion Detection System (HIDS) data analysis. In this paper, we conducted a comparative study on machine learning algorithms using LID-DS (Leipzig Intrusion Detection-Data Set) host-based intrusion detection data including thread information, metadata, and buffer data missing from previously used data sets. The algorithms used were Decision Tree, Naive Bayes, MLP (Multi-Layer Perceptron), Logistic Regression, LSTM (Long Short-Term Memory model), and RNN (Recurrent Neural Network). Accuracy, accuracy, recall, F1-Score indicators and error rates were measured for evaluation. As a result, the LSTM algorithm had the highest accuracy.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.177-186
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• 2021

The 2015 revised curriculum is structured around the core competencies of the 21st century, this is in line with the world's flow of education, such as OECD Education 2030. A future practical leading model was studied to provide a variety of creative teaching and learning experiences to elementary and Secondary students using intelligent information technology to cultivate core competencies such as ICT and computing thinking. In order for this practical model to stably settle the school field, the training was planned and operated to strengthen the creative convergence education capacity required by the teachers at the unit school through various types of the training. In particular, a nationwide administrators training program was operated for three years, reflecting the new curriculum, teaching and learning methods, and evaluation that can lead to future convergence talent training. In this paper, the perception of creative convergence education was investigated and analyzed considering the influence that administrators may have on the school field. Based on this, through the three-year operation results of the training, it was intended to establish a new training method for stable access to future creative convergence education under the post-corona era's social issues.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.380-389
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• 2022

Service design refers to an activity to design a user's service experience and a design area for professionally executing it. In order to design services from the people's point of view away from the supplier-oriented policy decisions in the past, the recent public participation business model using the service design methodology is increasing. In particular, the Ministry of Public Administration and Security formed the 'National Design Team' in 2014 to design services from the perspective of the public throughout the policy process. The public participatory policy model is being operated in which the public as policy consumers, service designers and public officials as suppliers participate in the overall policy process to develop and develop public services through service design techniques. This study is meaningful in that it presented the developmental direction of the actual project site through the case of the National Design Team sign improvement project with the goal of establishing a regional revitalization strategy using the service design methodology. However, as this study is about the current project, verification of the application of future project sites and user satisfaction evaluation have not been conducted. When the project is completed in the future, it is necessary to conduct a project satisfaction survey targeting consumers.