• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.21-32
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• 2021

Due to the recent development in electronic financial services, transactions of electronic prepayment are rapidly increasing. The increased transactions of electronic prepayment, however, also leads to the increased fraud attempts. It is mainly because electronic prepayment can easily be converted into cash. The objective of this paper is to develop a methodology that can effectively detect fraud transactions in electronic prepayment, by using sequential pattern mining techniques. To validate our approach, experiments on real transaction data were conducted and the applicability of the proposed method was demonstrated. As a result, the accuracy of the proposed method has been 95.6 percent, showing that the proposed method can effectively detect fraud transactions. The proposed method could be used to reduce the damage caused by the fraud attempts of electronic prepayment.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.6
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• pp.7-14
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• 2019

The automatic monitoring and detection of crowd behavior in the surveillance videos has obtained significant attention in the field of computer vision due to its vast applications such as security, safety and protection of assets etc. Also, the field of crowd analysis is growing upwards in the research community. For this purpose, it is very necessary to detect and analyze the crowd behavior. In this paper, we proposed a deep learning-based method which detects abnormal activities in surveillance cameras installed in a smart city. A fine-tuned VGG-16 model is trained on publicly available benchmark crowd dataset and is tested on real-time streaming. The CCTV camera captures the video stream, when abnormal activity is detected, an alert is generated and is sent to the nearest police station to take immediate action before further loss. We experimentally have proven that the proposed method outperforms over the existing state-of-the-art techniques.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.6
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• pp.151-158
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• 2019

FLUSH+RELOAD attack exposes the most serious security threat among cache side channel attacks due to its high resolution and low noise. This attack is exploited by a variety of malicious programs that attempt to leak sensitive information. In order to prevent such information leakage, it is necessary to detect FLUSH+RELOAD attack in real time. In this paper, we propose a novel run-time detection technique for FLUSH+RELOAD attack by utilizing PCM (Performance Counter Monitor) of processors. For this, we conducted four kinds of experiments to observe the variation of each counter value of PCM during the execution of the attack. As a result, we found that it is possible to detect the attack by exploiting three kinds of important factors. Then, we constructed a detection algorithm based on the experimental results. Our algorithm utilizes machine learning techniques including a logistic regression and ANN(Artificial Neural Network) to learn from different execution environments. Evaluation shows that the algorithm successfully detects all kinds of attacks with relatively low false rate.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.15 no.1
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• pp.28-32
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• 2019

In nuclear power plant operation and spent fuel canisters, it is necessary to provide a sound technical basis for the safety and security of long-term operation and storage respectively. Recently, the peening technology is being discussed and the technology will be adopted to ASME Section III, Division 1, Subsection NX (2019 Edition). The peening is prohibited in current edition, but it will be approved in 2019 Edition and adopted. However, Surface stress improvement techniques such as the peening is used to mitigate SCC susceptible in operating nuclear plants. Although the peening will be approved to ASME CODE, there are no performance criteria listed in the 2019 edition. The Korean International Working Group (KIWG) formed a new Task Group named "Advanced Surface Stress Improved Technology". The task group will develop a CODE CASE to address PWSCC(Primary Water Stress Corrosion Cracking) and CISCC(Chloride Induced Stress Corrosion Cracking) for new ASME Section III components. TG-ASSIT was started to make peening performance criteria for ASME Section III (new fabrication) applications. The objective of TG-ASSIT is to gain consensus among the relevant Code groups that requirements/mitigation have been met.

• Journal of the Korea Convergence Society
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• v.10 no.10
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• pp.21-26
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• 2019

At present, it is indispensable to utilize data as an information society. Therefore, the database is used to manage large amounts of data. In real life, most of the data in a database is the personal information of a group of members. Because personal information is sensitive data, the role of the database administrator who manages personal information is important. However, there is a growing number of attacks on databases to use this personal information in a malicious way. SQL Injection is one of the most known and old hacking techniques. SQL Injection attacks are known as an easy technique, but countermeasures are easy, but a lot of efforts are made to avoid SQL attacks on web pages that require a lot of logins, but some sites are still vulnerable to SQL attacks. Therefore, this study suggests effective defense measures through analysis of SQL hacking technology cases and contributes to preventing web hacking and providing a secure information communication environment.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.8
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• pp.311-318
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• 2021

Research has been ongoing to detect ships from offshore photographs for a variety of reasons, including maritime security, identifying international trends, and social scientific research. Due to the development of artificial intelligence, R-CNN models for object detection in photographs and images have emerged, and the performance of object detection has risen dramatically. Ship detection in offshore photographs using the R-CNN model has also begun to apply to satellite photography. However, satellite images project large areas, so various objects such as vehicles, landforms, and buildings are sometimes recognized as ships. In this paper, we propose a novel methodology to improve the performance of ship detection in satellite photographs using R-CNN series models. We separate land and sea via marker-based watershed algorithm and perform morphology operations to specify RoI one more time, then detect vessels using R-CNN family models on specific RoI to reduce typology. Using this method, we could reduce the misdetection rate by 80% compared to using only the Fast R-CNN.

• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.21-30
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• 2021

With the development of IoT technology, various cloud computing-based services such as smart cars, smart healthcare, smart homes, and smart farms are expanding. With the advent of a new environment, various problems continue to occur, such as the possibility of exposure of important information such as personal information or company secrets, financial damage cases due to hacking, and human casualties due to malicious attack techniques. In this paper, we propose a message communication protocol for smart home-based secure communication and user data protection. As a detailed process, secure device registration, message authentication protocol, and renewal protocol were newly designed in the smart home environment. By referring to the security requirements related to the smart home service, the stability of the representative attack technique was verified, and as a result of performing a comparative analysis of the performance, the efficiency of about 50% in the communication aspect and 25% in the signature verification aspect was confirmed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.904-913
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• 2020

As the data volumes and complexity rapidly increase, data-intensive science handling large-scale scientific data needs to investigate new techniques for intelligent storage and data distribution over networks. Recently, Named Data Networking (NDN) and data-intensive science communities have inspired innovative changes in distribution and management for large-scale experimental data. In this article, analysis on NDN testbeds for large-scale scientific data such as climate science data and High Energy Physics (HEP) data is presented. This article is the first attempt to analyze existing NDN testbeds for large-scale scientific data. NDN testbeds for large-scale scientific data are described and discussed in terms of status, NDN-based application, and features, which are NDN testbed instance for climate science, NDN testbed instance for both climate science and HEP, and the NDN testbed in SANDIE project. Finally various issues to prevent pitfalls in NDN testbed establishment for large-scale scientific data are analyzed and discussed, which are drawn from the descriptions of NDN testbeds and features on them.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.280-285
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• 2021

When VNDN technology is used as a communication technology for infotainment application services of connected vehicles, it is possible to realize data-centric networking technology in which data is the subject of communication.Vehicle security attacks and hacks, performance degradation during long-distance data transmission, and frequent data loss It is possible to innovate the limitations of the current host-oriented Internet-based infotainment application service technology of connected vehicles. The data packet forwarding issue to deliver critical information data that is very sensitive to delay in the VNDN on a push-based basis to RSU (Road Side Unit), etc. is one of the issues to be solved for realizing VNDN-based application services. We comprehensively analyze existing forwarding techniques to support push-based data traffic under the environment, and compare and analyze each technique in terms of performance.

• New & Renewable Energy
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• v.18 no.2
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• pp.73-81
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• 2022

This study was aimed at designing a condenser, as a component of the organic Rankine cycle system for ships. The condenser was manufactured through press molding to achieve a bent shape to enhance the heat transfer performance, considering the shape of the heat transfer plate used in a brazing plate heat exchanger. The heat transfer plate was made of copper-nickel alloy. The required heat transfer rate for the condenser was 110 kW, and the maximum number of layers was set as 25, considering the characteristics of high-temperature brazing. Computational fluid dynamics techniques were used to perform the thermal fluid analysis, based on the ANSYS CFX (v.18.1) commercial program. The heat transfer rate of the condenser was 4.96 kW for one layer (width and length of 0.224 and 0.7 m, respectively) of the heat transfer exchanger. The fin efficiency pertaining to the heat transfer plate was approximately 20%. The heat flow analysis for one layer of the heat exchanger plate indicated that the condenser with 25 layers of heat transfer plates could achieve a heat transfer rate of 110 kW.