• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.1
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• pp.25-38
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• 2022

With the diversification of payment methods and games, related financial accidents are causing serious problems for users and game companies. Recently, game companies have introduced an Fraud Detection System (FDS) for game payment systems to prevent financial incident. However, FDS is ineffective and cannot provide major evidence based on judgment results, as it requires constant change of detection patterns. In this paper, we analyze abnormal transactions among payment log data of real game companies to generate related features. One of the unsupervised learning models, Autoencoder, was used to build a model to detect abnormal transactions, which resulted in over 85% accuracy. Using X-FDS (Explainable FDS) with XAI-SHAP, we could understand that the variables with the highest explanation for anomaly detection were the amount of transaction, transaction medium, and the age of users. Based on X-FDS, we derive an improved detection model with an accuracy of 94% was finally derived by fine-tuning the importance of features that adversely affect the proposed model.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.6
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• pp.1069-1086
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• 2013

Nowadays, web defacement becomes the utmost threat which can harm the target organization's image and reputation. These defacement activities reflect the hacker's political motivation or his tendency. Therefore, the analysis of the hacker's activities can give the decisive clue to pursue criminals. A specific message or photo or music on the defaced web site and the outcome of analysis will be supplying some decisive clues to track down criminals. The encoding method or used fonts of the remained hacker's messages, and hacker's SNS ID such as Twitter or Facebook ID also can help for tracking hackers information. In this paper, we implemented the web defacement analysis system by applying CBR algorithm. The implemented system extracts the features from the web defacement cases on zone-h.org. This paper will be useful to understand the hacker's purpose and to plan countermeasures as a IDSS(Investigation Detection Support System).

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.771-782
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• 2021

Regular or irregular situations such as traffic accidents, damage to road facilities, maintenance or repair work, and vehicle breakdowns occur frequently on highways. It is required to provide traffic services to drivers by promptly recognizing these regular or irregular situations, various techniques have been developed for rapidly collecting data and detecting abnormal traffic conditions to solve the problem. We propose a method that can be used for verification and demonstration of unexpected situation algorithms by establishing a system and developing algorithms for detecting unexpected situations on highways. For the detection of emergencies on expressways, a system was established by defining the expressway contingency and algorithm development, and a test bed was operated to suggest a method that can be used for verification and demonstration of contingency algorithms. In this study, a system was established by defining the unexpected situation and developing an algorithm to detect the unexpected situation on the highway, and a method that can be used verifying and demonstrating unexpected situations. It is expected to secure golden time for the injured by reducing the effectiveness of secondary accidents. Also predictable accidents can be reduced in case of unexpected situations and the detection time of unpredictable accidents.

• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.522-530
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• 2014

Spatio-temporal congestion evolution pattern can be reproduced using the VDS(Vehicle Detection System) historic speed dataset in the TMC(Traffic Management Center)s. Such dataset provides a pool of spatio-temporally experienced traffic conditions. Traffic flow pattern is known as spatio-temporally recurred, and even non-recurrent congestion caused by incidents has patterns according to the incident conditions. These imply that the information should be useful for traffic prediction and traffic management. Traffic flow predictions are generally performed using black-box approaches such as neural network, genetic algorithm, and etc. Black-box approaches are not designed to provide an explanation of their modeling and reasoning process and not to estimate the benefits and the risks of the implementation of such a solution. TMCs are reluctant to employ the black-box approaches even though there are numerous valuable articles. This research proposes a more readily understandable and intuitively appealing data-driven approach and developes an algorithm for identifying congestion patterns for recurrent and non-recurrent congestion management and information provision.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.17 no.3
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• pp.261-269
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• 2004

The existing concrete beams can be retrofitted or reinforced by attaching carbon fiber or glass fiber sheet beneath the beams. Although diverse design methods and application techniques of the retrofitting are studied and developed, the testing method of examining retrofitted beams have not been put into practice yet. In this study, a bond delamination has been modeled and studied to provide a basis for the development of actual testing equipments. For this purpose, Gaussian and sinusoidal waves with 3GHz and 5GHz center frequency are used as an incident wave and 1mm and 3mm bond delamination under the reinforcement are modeled. In the modeling, Finite Difference-Time Domain algorithm is used to investigate the behavior of electromagnetic waves in concrete. The results have shown that 5GHz waves are suitable for the detection of delamination.

• Journal of Radiation Protection and Research
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• v.43 no.3
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• pp.85-96
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• 2018

Background: A variety of inorganic scintillators have been developed and improved for use in radiation detection and measurement, and in situ gamma-ray spectrometry in the environment remains an important area in nuclear safety. In order to verify the feasibility of promising scintillators in an actual environment, a performance test is necessary to identify gamma-ray peaks and calculate the radioactivity from their net count rates in peaks. Materials and Methods: Among commercially available scintillators, $LaBr_3(Ce)$ scintillators have so far shown the highest energy resolution when detecting and identifying gamma-rays. However, the intrinsic background of this scintillator type affects efficient application to the environment with a relatively low count rate. An algorithm to subtract the intrinsic background was consequently developed, and the in situ calibration factor at 1 m above ground level was calculated from Monte Carlo simulation in order to determine the radioactivity from the measured net count rate. Results and Discussion: The radioactivity of six natural radionuclides in the environment was evaluated from in situ gamma-ray spectrometry using an $LaBr_3(Ce)$ detector. The results were then compared with those of a portable high purity Ge (HPGe) detector with in situ object counting system (ISOCS) software at the same sites. In addition, the radioactive cesium in the ground of Jeju Island, South Korea, was determined with the same assumption of the source distribution between measurements using two detectors. Conclusion: Good agreement between both detectors was achieved in the in situ gamma-ray spectrometry of natural as well as artificial radionuclides in the ground. This means that an $LaBr_3(Ce)$ detector can produce reliable and stable results of radioactivity in the ground from the measured energy spectrum of incident gamma-rays at 1 m above the ground.

• Journal of the Korea Convergence Society
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• v.8 no.7
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• pp.1-6
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• 2017

This paper presents the design of a frequency measurement device using ADC, EP2AGX FPGA and STM32 processor to accurately measure the frequency of a broadband high frequency signal. The ADC device used in this paper has a sampling frequency of 250 MSPS and a processing frequency bandwidth of 100 MHz. Due to its high sampling frequency, it is difficult to process in ordinary computers or processors, so we implemented the frequency measurement algorithm using the Altra EP2AGX FPGA. The measured frequency is sent to the direction detection controller in real time and fused with the phase signal to calculate the incident azimuth angle of the high frequency signal. The designed frequency measurement device is about 0.2 Mhz in frequency measurement error and 30% less than Anaren DFD-x, which is considered to contribute greatly to the design of radio monitoring and direction detection device.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.2
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• pp.1-8
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• 2011

Traffic congestion is a source of significant economic and social costs in urban areas. Intelligent Transportation Systems (ITS) are a promising means to help alleviate congestion by utilizing advanced sensing, computing, and communication technologies. This paper proposes and investigates a basic and advanced ITS framework Advanced Traveler Information System (ATIS) using wireless Vehicle to Roadside (Centralized ATIS model: CA model) and Vehicle to Vehicle (DeCentralized ATIS model: DCA model) communication and assuming an ideal communication environment in the typical $6{\times}6$ urban grid traffic network. Results of this study indicate that an ATIS using wireless communication can save travel time given varying combinations of system characteristics: traffic flow, communication radio range, and penetration ratio. Also, all tested metrics of the CA and DCA models indicate that the system performance of both models is almost identical regardless of varying traffic demand and penetration ratios. Therefore, DCA model can be a reasonable alternative to the fixed infrastructure based ATIS model (CA model).

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.41-47
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• 2012

Every object over $O^{\circ}K$ emits radiant energy based on its own temperature. Uncooled thermal imaging system displays the detected incident radiant energy as an image by signal processing. Recently, the uncooled thermal imaging system is applied to various areas such as medical, industrial, and military applications. Also, several researches are in progress to find new applications of the uncooled thermal imaging system. In this paper, we present effective method for controlling TEC-less detector in the uncooled thermal imaging system and also present the efficient control scheme for maximizing the accuracy of temperature measurement. The proposed scheme is to apply TEC-less and temperature detection algorithm in Uncooled thermal imaging system. In results of tests performed by using the actual chamber, we acquired images of better quality than the former system and temperature measurement accuracy was improved to less than $1^{\circ}C$.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.363-368
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• 2003

We have successfully developed a more effective algorithm to extract the lineament in the area covered by wide alluvial deposits characterized by a relatively narrow range of brightness in the Landsat TM image, while the currently used algorithm is limited to the mountainous areas. In the new algorithm, flat areas mainly consisting of alluvial deposits were selected using the Local Enhancement from the Digital Elevation Model (DEM). The aspect values were obtained by 3${\times}$3 moving windowing of Zevenbergen & Thorno's Method, and then the slopes of the study area were determined using the aspect values. After the lineament factors in the alluvial deposits were revealed by comparing the threshold values, the first rank lineament under the alluvial deposits were extracted using the Hough transform In order to extract the final lineament, the lowest points under the alluvial deposits in a given topographic section perpendicular to the first rank lineament were determined through the spline interpolation, and then the final lineament were chosen through Hough transform using the lowest points. The algorithm developed in this study enables us to observe a clearer lineament in the areas covered by much larger alluvial deposits compared with the results extracted using the conventional existing algorithm. There exists, however, some differences between the first rank lineament, obtained using the aspect and the slope, and the final lineament. This study shows that the new algorithm more effectively extracts the lineament in the area covered with wide alluvlal deposits than in the areas of converging slope, areas with narrow alluvial deposits or valleys.