• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.22 no.4
• /
• pp.785-796
• /
• 2012

In this paper, we propose an effective Behavior-based detection technique using the frequency of system calls to detect malicious code, when the number of training data is fewer than the number of properties on system calls. In this study, we collect the Native APIs which are Windows kernel data generated by running program code. Then we adopt the normalized freqeuncy of Native APIs as the basic properties. In addition, the basic properties are transformed to new properties by GLDA(Generalized Linear Discriminant Analysis) that is an effective method to discriminate between malicious code and normal code, although the number of training data is fewer than the number of properties. To detect the malicious code, kNN(k-Nearest Neighbor) classification, one of the bayesian classification technique, was used in this paper. We compared the proposed detection method with the other methods on collected Native APIs to verify efficiency of proposed method. It is presented that proposed detection method has a lower false positive rate than other methods on the threshold value when detection rate is 100%.

• Journal of the Korean Institute of Gas
• /
• v.14 no.1
• /
• pp.37-41
• /
• 2010

The most important element for improving the process safety that occurs from the flare system installed to convert into safe materials by burning the inflammable or toxic gases within the process and this is specified in the API 521 Code so that the radiation does not cause a risk factor. The flames that occur from the flare stack holds the shape of jet fire due to the pressure and flow velocity of discharge gas. This study has identified the shape of flames by using the Chamberlain Model rather than the API 521 Code method, analyzing the radiation due to this.

• Korean Journal of Computational Design and Engineering
• /
• v.19 no.4
• /
• pp.368-389
• /
• 2014

There are many agendas and discussion subjects for BIM-based Criteria Design phase. At that time, some problems are occurred by software compatibility, simple repetitive tasks, rework caused by missing information etc. In this study, we focus on solving that problems by applying API(Application Programming Interface) method. For effective study, we construct Criteria Design process by using DSM (Dependency Structure Matrix) and study applicability of API. It will be effective for time-consuming task and simply labor-intensive tasks by applying API. we expect improving BIM-based Design Process and Data quality, work productivity without missing information and shapes for using API.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.6
• /
• pp.1375-1382
• /
• 2019

The latest version of commercial protector, Themida, has been updated, it is impossible to apply a normalized unpacking mechanism from previous studies by disable the use of a virtual memory allocation that provides initial data to be tracked. In addition, compared to the previous version, which had many values that determined during execution and easy to track dynamically, it is difficult to track dynamically due to values determined at the time of applying the protector. We will look at how the latest version of Themida make it difficult to normalize the API wrapping process by adopted techniques and examine the possibilities of applying the unpacking techniques to further develop an automated unpacking system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2011.10a
• /
• pp.551-553
• /
• 2011

The popularization and development of 3D display makes common users easy to experience a solid 3D virtual reality, the demand for virtual reality contents are increasing. This paper proposes VR panorama system using vanishing point location-based depth map generation method. VR panorama using depth map gives an effect that makes users feel staying at real place and looking around nearby circumstances.

• Korean Journal of Food Science and Technology
• /
• v.52 no.6
• /
• pp.678-684
• /
• 2020

The objective of this study was to identify the fermentation characteristics of Bacillus thuringiensis and emetic, non-emetic Bacillus cereus using analytical profile index (API) test. Ten strains of B. thuringiensis and 10 strains of B. cereus including 3 strains of emetic type were used at the same concentrations. The differences of fermentation characteristics between the B. thuringiensis and B. cereus was not obvious, but the differences between the non-emetic and emetic B. cereus were distinctive. Seven among 50 substrates were negative for all non-emetic B. cereus strains and positive for all emetic strains, and three substrates among additional 12 substrates had the same tendency. From these differences, 3 emetic B. cereus strains were not indicated as B. cereus by API test. These results indicate that API test is not a suitable method to identify some strains of emetic B. cereus, and the distinctive differences in substrate utilization can be used to improve selective media.

• Journal of the Korean Geotechnical Society
• /
• v.34 no.7
• /
• pp.51-58
• /
• 2018

In this study a series of centrifuge tests were carried out in dry sand to analyze the comparison of lateral pile behavior for static loading and dynamic loading condition. In case of static loading condition, the lateral displacement was applied up to 50% of pile diameter by deflection control method. And the input sine wave of 0.1 g~0.4 g amplitude and 1 Hz frequency was applied at the base of the soil box using shaking table for dynamic loading condition. From comparison of experimental static p-y curve obtained from static loading tests with API p-y curves, API p-y curves can predict well within 20% error the ultimate subgrade reaction force of static loading condition. The ultimate subgrade reaction force of experimental dynamic p-y curve is 5 times larger than that of API p-y curves and experimental static p-y curves. Therefore, pseudo-static analysis applied to existing p-y curve for seismic design could greatly underestimate the soil resistance at non-linear domain and cause overly conservative design.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.22 no.4
• /
• pp.363-370
• /
• 2009

We simulated large deformation and inelastic behavior of API-X80 steel linepipes using nonlinear finite element method. Gurson-Tvergaard-Needleman(GTN) model is employed for the development of the constitutive model of the steel. The GTN model is implemented in the form of the user-supplied material subroutine(UMAT) for the commercial software of ABAQUS. To calibrate the model parameters, we simulated the behavior of the uniaxial tension test using ABAQUS equipped with the developed GTN model. Using the set of the model parameters, we were able to capture the characteristics of the plastic buckling of API-X80 steel linepipes.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.2
• /
• pp.644-662
• /
• 2023

There are still outbreaks of COVID-19 across the world. Ships increase the risk of worldwide transmission of the virus. Close contact tracing remains as an effective method of reducing the risk of virus transmission. Therefore, close contact tracing in ship environments becomes a research topic. Exposure Notifications API (Application Programming Interface) can be used to determine the encountered location points of close contacts on ships. Location points of close contact are estimated by the encountered location points. Risky areas in ships can be calculated based on the encountered location points. The tracking of close contacts is possible with Bluetooth technology without the Internet. The Bluetooth signal can be used to judge the proximity among detecting devices by using the feature that Bluetooth has a strong signal at close range. This Bluetooth feature makes it possible to trace close contacts in ship environments. In this paper, we propose a method for close contact tracing and showing the risky area in a ship environment by combining beacon and Exposure Notification API using Bluetooth technology. This method does not require an Internet connection for tracing close contacts and can protect the personal information of close contacts.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.11
• /
• pp.41-49
• /
• 2021

All application programs, including malware, call the Application Programming Interface (API) upon execution. Recently, using those characteristics, attempts to detect and classify malware based on API Call information have been actively studied. However, datasets containing API Call information require a large amount of computational cost and processing time. In addition, information that does not significantly affect the classification of malware may affect the classification accuracy of the learning model. Therefore, in this paper, we propose a method of extracting a essential feature set after reducing the dimensionality of API Call information by applying various feature selection methods. We used CICAndMal2020, a recently announced Android malware dataset, for the experiment. After extracting the essential feature set through various feature selection methods, Android malware classification was conducted using CNN (Convolutional Neural Network) and the results were analyzed. The results showed that the selected feature set or weight priority varies according to the feature selection methods. And, in the case of binary classification, malware was classified with 97% accuracy even if the feature set was reduced to 15% of the total size. In the case of multiclass classification, an average accuracy of 83% was achieved while reducing the feature set to 8% of the total size.