• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.2
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• pp.179-188
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• 2012

Packing techniques, one of malicious code detection and analysis avoidance techniques, change code to reduce size and make analysts confused. Therefore, malwares have more time to spread out and it takes longer time to analyze them. Thus, these kind of unpacking techniques have been studied to deal with packed malicious code lately. Packed programs are unpacked during execution. When it is unpacked, the data inside of the packed program are changed. Because of these changes, the entropy value of packed program is changed. After unpacking, there will be no data changes; thus, the entropy value is not changed anymore. Therefore, packed programs could be unpacked finding the unpacking point using this characteristic regardless of packing algorithms. This paper suggests the generic unpacking mechanism using the method estimating the unpacking point through the variation of entropy values.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.227-234
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• 2023

In this paper, we developed a design thinking-based artificial intelligence education program for middle school students and applied it to verify the impact on creative problem-solving skills. The inspection tool used the Creative Problem Solving Profile Inventory (CPSPI), an inspection tool for measuring creative thinking type ability based on the CPS theory of Hwasun Lee, Jungmin Pyo, Insoo Choe(2014). CPSPI included the steps of evaluating cognitive preferences and cognitive abilities by supplementing the limitations of existing tests, and sharing and persuading one's ideas with others. Before and after applying the design thinking-based artificial intelligence education program, as a result of analyzing the creative problem-solving ability, it increased significantly in all areas. As a result of analyzing the creative problem-solving ability of middle school students, significant results were found in the areas of Problem Detection and Analysis, Idea Generation, Action plan, Execution, Persuasion and Communication. The effect of design thinking was confirmed as a teaching and learning method to improve creative problem-solving ability in artificial intelligence education.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1581-1587
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• 2021

As embedded system are used widely and variously, multi-edge system, which multiple edges gather and perform complex operations together, is actively operating. In a multi-edge system, it often occurs that an abnormal operation at one edge is transferred to another edge or the entire system goes down. It is necessary to determine and control edge anomalies in order to prevent system down, but this can be a heavy burden on the resource-limited edge. As a solution to this, we use power consumption data to check the state of the edge device and transmit it based on a QRcode to check and control errors at the server. The architecture proposed in this paper is implemented using 'chip-whisperer' to measure the power consumption of the edge and 'Raspberry Pi 3' to implement the server. As a result, the proposed architecture server showed successful data transmission and error determination without additional load appearing at the edge.

• Journal of Korean Dental Hygiene Science
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• v.5 no.1
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• pp.21-27
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• 2022

Background: This study was conducted to analyze the time for re-detection of bacteria after surface disinfection using wet wipes, isopropyl alcohol, and benzalkonium chloride antibacterial tissue and provide standards for re-execution of surface disinfection with wet and antibacterial tissues. Methods: Seven laptops were wiped with wet tissue and isopropyl alcohol and benzalkonium chloride antibacterial tissues. Test areas were rubbed with a sterile cotton swab at baseline and after 30, 60, and 120 min. After plating on a tryptic soy agar medium, the number of colonies was counted by culturing at 36.5℃ for 24 h. Results: The average number of bacterial colonies was 5.85 ± 4.33 before isopropyl alcohol wiping and nil after wiping. The average number of bacterial colonies was 12.28 ± 14.67 benzalkonium chloride wiping and nil after wiping. Before wiping with wet wipes, the average number of bacterial colonies on laptop surfaces was 3.42 ± 5.22. Bacteria decreased after wiping with wet wipes but increased again over time. Conclusions: Wet wipes can temporarily reduce bacteria but are unsuitable for removing bacteria.

• Convergence Security Journal
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• v.23 no.1
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• pp.117-123
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• 2023

To detect advanced ransomware attacks with machine learning-based models, the classification model must train learning data with high-dimensional feature space. And in this case, a 'curse of dimension' phenomenon is likely to occur. Therefore, dimensionality reduction of features must be preceded in order to increase the accuracy of the learning model and improve the execution speed while avoiding the 'curse of dimension' phenomenon. In this paper, we conducted classification of ransomware by applying three machine learning models and two feature extraction techniques to two datasets with extremely different dimensions of feature space. As a result of the experiment, the feature dimensionality reduction techniques did not significantly affect the performance improvement in binary classification, and it was the same even when the dimension of featurespace was small in multi-class clasification. However, when the dataset had high-dimensional feature space, LDA(Linear Discriminant Analysis) showed quite excellent performance.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.495-501
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• 2023

P-3C/K aircraft for maritime patrols that Republic of Korea Navy is using, is equipped with a variety of sensors and communication devices. Collected data from the aircraft is managed as tactical information by flight operators and stored. When the flight mission is completed, this information is transferred to tactical support center on the ground and played back or used for follow-up work through a analysis tool. During a flight mission, there are tens of thousands of detection objects within an hour in KADIZ (Korea air defense identification zone). In contrast, in TSD (tactical situation display), which displays a map when using the analysis tool, all detected objects are expressed as symbols. The increase in display symbols has a significant impact on the TSD image updating and consequently interferes with the smooth operation of operators. In this paper, we propose applying multiple threads and multiple layers to improve the performance of existing TSD. And the performance improvement is proven through the execution results.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.307-314
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• 2023

As supercomputing and hardware technology advances, climate prediction models are improving. The Korean Meteorological Administration adopted GloSea5 from the UK Met Office and now operates an updated GloSea6 tailored to Korean weather. Universities and research institutions use Low-GloSea6 on smaller servers, improving accessibility and research efficiency. In this paper, profiling Low-GloSea6 on smaller servers identified the tri_sor_dp_dp subroutine in the tri_sor.F90 atmospheric model as a CPU-intensive hotspot. Applying linear regression, a type of machine learning, to this function showed promise. After removing outliers, the linear regression model achieved an RMSE of 2.7665e-08 and an MAE of 1.4958e-08, outperforming Lasso and ElasticNet regression methods. This suggests the potential for machine learning in optimizing identified hotspots during Low-GloSea6 execution.

• Journal of Internet Computing and Services
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• v.11 no.6
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• pp.61-72
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• 2010

Spectrum scarcity problem and increasing spectrum demand for new wireless applications have embossed the importance of cognitive radio technology; the technology enables the sharing of channels among secondary (unlicensed) and primary (licensed) users on a non-interference basis after sensing the vacant channel. To enhance the accuracy of sensing, distributed spectrum sensing is proposed. However, it is necessary to provide the robustness against the compromised sensing nodes in the distributed spectrum sensing. RDSS, a fusion mechanism based on the reputation of sensing nodes and WSPRT (weighted sequential probability ratio test), was proposed. However, in RDSS, the execution number of WSPRT could increase according to the order of inputted sensing values, and the fast defense against the forged values is difficult. In this paper, we propose an enhanced fusion mechanism to input the sensing values in reputation order and exclude the sensing values with the high possibility to be compromised, using the trend of reputation variation. We evaluate our mechanism through simulation. The results show that our mechanism improves the robustness against attack with the smaller number of sensing values and more accurate detection ratio than RDSS.

• The Journal of the Acoustical Society of Korea
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• v.19 no.3
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• pp.51-56
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• 2000

Is this paper, we studied on the automatic speech control system in real-time windows environment using voice recognition. The applied reference pattern is the variable DMS model which is proposed to fasten execution speed and the one-stage DP algorithm using this model is used for recognition algorithm. The recognition vocabulary set is composed of control command words which are frequently used in windows environment. In this paper, an automatic speech period detection algorithm which is for on-line voice processing in windows environment is implemented. The variable DMS model which applies variable number of section in consideration of duration of the input signal is proposed. Sometimes, unnecessary recognition target word are generated. therefore model is reconstructed in on-line to handle this efficiently. The Perceptual Linear Predictive analysis method which generate feature vector from extracted feature of voice is applied. According to the experiment result, but recognition speech is fastened in the proposed model because of small loud of calculation. The multi-speaker-independent recognition rate and the multi-speaker-dependent recognition rate is 99.08% and 99.39% respectively. In the noisy environment the recognition rate is 96.25%.

• Journal of KIISE:Databases
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• v.30 no.2
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• pp.197-208
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• 2003

Abstract Workflow is not appropriately applied to coordinated execution of applications(steps) that comprise business process such as a collaborative series of tasks because of the lacks of network infra, standard of information exchange and data consistency management with conflict mode of shared data. Particularly we have not mentioned the problem which can be occurred by shared data with conflict mode. In this paper, to handle data consistency in the process of rollback for failure handling or recovery policy, we have classified rollback dependency into three types such as implicit rollback dependency in a transactional workflow, implicit rollback dependency in collaborative transactional workflows and explicit rollback dependency in collaborative transactional workflows. Also, we have proposed the rollback dependency compiler that determines above three types of rollback dependency. A workflow designer specifies the workflow schema and the resources accessed by the steps from a global database of resources. The rollback dependency compiler generates the enhanced workflow schema with the rollback dependency specification. The run-time system interprets this specification and executes the rollback policy with data consistency if failure of steps is occurred. After all, this paper can offer better correctness and performance than state-of-the-art WFMSs.