• The KIPS Transactions:PartC
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• v.16C no.4
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• pp.461-476
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• 2009

Digital Printers that are mainly used in enterprises and public institutions are compound machinery and tools which are combined into various functions such as printing, copying, scanning, and fax so on. Digital Printers has security functionality for protecting the important data related with confidential industry technology from leaking. According to the trends, CC(Common Criteria) evaluation and assurance about digital printer is on progress in Japan and USA. Domestically CC evaluation and assurance is started recently. However, the know-how about the digital printer evaluation is not enough and the developers and the evaluators have difficulty in CC evaluation of digital printer products in the country. Therefore, the testing method of digital printer security functionality and evaluation technology is essentially needed for increasing demand for the evaluation afterwards. In this study, we analyze the security functionality and developing trends of digital printer products from internal and external major digital printer companies. Moreover, we research the characters of each security functions and propose guideline for digital printer security functionality evaluation and vulnerability testing methods.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.2
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• pp.86-99
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• 2007

Packet filtering is to filter out potentially malicious network packets. In order to test a packet filtering function we should verify whether security policies are performed correctly as intended. However there are few existing tools to test the function. Besides, they need user participation when generating test cases or deciding test results. Many security administrators have a burden to test systematically new security policies when they establish new policies or modify the existing ones. To mitigate the burdens we suggest a new test method with minimal user articipation. Our tool automates generation steps of the test cases and the test oracles, respectively. By using the test oracles generated automatically, deciding test results is possible without user intervention. Our method realizes an automatic testing in three phases; test preparation phase, test execution, and test evaluation. As a result it may enhance confidence of test activities more highly. This paper describes the design and implementation of our test method and tool.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.157-164
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• 2021

The aim of this study is to provide empirical evaluation of the accuracy of data-model fit using growing levels of invariance models. Overall model accuracy of factor solutions was evaluated by the examination of the order for testing three levels of measurement invariance (MIV) starting with configural invariance (model 0). Model testing was evaluated by the Chi-square difference test (∆𝛘²) between two groups, and root mean square error of approximation (RMSEA), comparative fit index (CFI), and Tucker-Lewis index (TLI) were used to evaluate the all-model fits. Factorial invariance result revealed that stability of the models was varying over increasing levels of measurement as a function of variable-to-factor ratio (VTF), subject-to-variable ratio (STV), and their interactions. There were invariant factor loadings and invariant intercepts among the groups indicating that measurement invariance was achieved. For VTF ratio (3:1, 6:1, and 9:1), the models started to show accuracy over levels of measurement when STV ratio was 6:1. Yet, the frequency of stability models over 1000 replications increased (from 69% to 89%) as STV ratio increased. The models showed more accuracy at or above 39:1 STV.

• Journal of the Society of Naval Architects of Korea
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• v.57 no.6
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• pp.322-330
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• 2020

This study deals with underwater explosion (UNDEX) characteristics of various non-explosive underwater shock sources for the development of non-explosive underwater shock testing devices. UNDEX can neutralize ships' structure and the equipment onboard causing serious damage to combat and survivability. The shock proof performance of naval ships has been for a long time studied through simulations, but full-scale Live Fire Test and Evaluation (LFT&E) using real explosives have been limited due to the high risk and cost. For this reason, many researches have been tried to develop full scale ship shock tests without using actual explosives. In this study, experiments were conducted to find the characteristics of the underwater shock waves from actual explosive and non-explosive shock sources such as the airbag inflators and Vaporizing Foil Actuator (VFA). In order to derive the empirical equation for the maximum pressure value of the underwater shock wave generated by the non-explosive impact source, repeated experiments were conducted according to the number and distance. In addition, a Shock Response Spectrum (SRS) technique, which is a frequency-based function, was used to compare the response of floating bodies generated by underwater shock waves from each explosion source. In order to compare the magnitude of the underwater shock waves generated by each explosion source, Keel Shock Factor (KSF), which is a measure for estimating the amount of shock experienced by a naval ship from an underwater explosionan, was used.

• Journal of Korean Society of Disaster and Security
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• v.12 no.2
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• pp.73-82
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• 2019

Recently, as the occurrence frequency of sudden floods due to climate change increased, the flood damage on riverside social infrastructures was extended so that there has been a threat of overflow. Therefore, a rapid prediction of potential flooding in riverside social infrastructure is necessary for administrators. However, most current flood forecasting models including hydraulic model have limitations which are the high accuracy of numerical results but longer simulation time. To alleviate such limitation, data driven models using artificial neural network have been widely used. However, there is a limitation that the existing models can not consider the time-series parameters. In this study the water surface elevation of the Hangang River bridge was predicted using the NARX model considering the time-series parameter. And the results of the ANN and RNN models are compared with the NARX model to determine the suitability of NARX model. Using the 10-year hydrological data from 2009 to 2018, 70% of the hydrological data were used for learning and 15% was used for testing and evaluation respectively. As a result of predicting the water surface elevation after 3 hours from the Hangang River bridge in 2018, the ANN, RNN and NARX models for RMSE were 0.20 m, 0.11 m, and 0.09 m, respectively, and 0.12 m, 0.06 m, and 0.05 m for MAE, and 1.56 m, 0.55 m and 0.10 m for peak errors respectively. By analyzing the error of the prediction results considering the time-series parameters, the NARX model is most suitable for predicting water surface elevation. This is because the NARX model can learn the trend of the time series data and also can derive the accurate prediction value even in the high water surface elevation prediction by using the hyperbolic tangent and Rectified Linear Unit function as an activation function. However, the NARX model has a limit to generate a vanishing gradient as the sequence length becomes longer. In the future, the accuracy of the water surface elevation prediction will be examined by using the LSTM model.