• Journal of the Korea Society of Computer and Information
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• v.23 no.3
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• pp.55-62
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• 2018

In this paper, we propose a model to detect crowdfunding scams, which have been reportedly occurring over the last several years, based on their project information and linguistic features. To this end, we first collect and analyze crowdfunding scam projects, and then reveal which specific project-related information and linguistic features are particularly useful in distinguishing scam projects from non-scams. Our proposed model built with the selected features and Random Forest machine learning algorithm can successfully detect scam campaigns with 84.46% accuracy.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.124-133
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• 2022

With the development of hardware technology and the advancement of numerical model methods, more precise weather forecasts can be carried out. In this paper, we propose a Unicon Optimization scheme combining Loop Vectorization, Dependency Vectorization, and Code Modernization to optimize and increase Maintainability the Unicon source contained in SCAM, a simplified version of CESM, and present an overall SCAM structure. This paper tested the unicorn optimization scheme in the SCAM structure, and compared to the existing source code, the loop vectorization resulted in a performance improvement of 3.086% and the dependency vectorization of 0.4572%. And in the case of Unicorn Optimization, which applied all of these, the performance improvement was 3.457% compared to the existing source code. This proves that the Unicorn Optimization technique proposed in this paper provides excellent performance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.1
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• pp.33-40
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• 2023

With the development of supercomputing technology and hardware technology, numerical computation methods are also being advanced. Accordingly, improved weather prediction becomes possible. In this paper, we propose to apply the LAPACK(Linear Algebra PACKage) BLAS(Basic Linear Algebra Subprograms) library to the linear algebraic numerical computation part within the source code to improve the performance of the cumulative parametric code, Unicon(A Unified Convection Scheme), which is included in SCAM(Single-Columns Atmospheric Model, simplified version of CESM(Community Earth System Model)) and performs standby operations. In order to analyze this, an overall execution structure diagram of SCAM was presented and a test was conducted in the relevant execution environment. Compared to the existing source code, the SCOPY function achieved 0.4053% performance improvement, the DSCAL function 0.7812%, and the DDOT function 0.0469%, and all of them showed a 0.8537% performance improvement. This means that the LAPACK BLAS application method, a library for high-density linear algebra operations proposed in this paper, can improve performance without additional hardware intervention in the same CPU environment.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.3
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• pp.189-197
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• 2022

With the development of high-performance computing technology and the advancement of numerical model, it is possible to predict the better weather forecasting. The purpose of this paper is the performance improvement for the SCAM climate model for the model running time excluding the compilation time. Therefore, the model previously performed using the Intel Fortran Compiler was changed to PGI Fortran Compiler. To this end, we reconfigure system environment variables, reset compilation options, install dependencies SW and library, and modify source code. In addition, we proposed and applied the 'PGI Compile with OpenACC' method. As a result, when the compiler was changed from intel to PGI, it led to an improvement of 6.08% in running time and when the openACC method was applied, it led to an improvement of 43.05% in running time. This demonstrates that the PGI Compile with OpenACC method proposed in this paper leads to excellent performance.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.01a
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• pp.307-310
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• 2016

우리나라의 무역 교역량이 '11년부터 3년 연속 1조 달러를 돌파하면서 인터넷 무역도 활성화 되고 있으나 인터넷 무역의 특징인 비대면 거래과정을 악용한 사기 행위가 급증하여 기업의 피해가 증가하고 있는 실정이다. 이메일을 해킹하여 거래처로 위장해 무역 거래대금을 가로채는 사이버범죄 수법인 비즈니즈 스캠(Business Scam)은 건전한 무역 활동에 위협적인 요소로 작용하고 있다. 이와 같이 무역 산업의 위협이 증가하고 있는 현재 상황에서 본 연구는 정보보호 관점에서 기술, 정책, 제도, 법률, 관련 사례를 조사 분석하여 비즈니스 스캠의 효율적인 피해방지 방안을 제시하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.554-555
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• 2024

전세 사기로 인한 피해가 해마다 증가하고 있다. 본 연구에서는 부동산 가격과 대출 데이터를 통해 전세 사기의 원인을 분석하고, 이에 대한 대처방안을 제시하였다. 데이터 분석 결과, 주택 가격의 상승과 부동산 정책의 변화가 전세사기에 주요한 영향을 미친다는 것과, 전세사기 사건 수와 부동산 가격 상승 사이에 높은 상관관계가 나타남을 확인했다. 또한, 회귀분석을 사용하여 연도에 따른 전세보증사고 금액 예측 모델을 구축하였다. 이를 토대로 부동산 시장 안정화와 함께 개인 및 정부 차원의 협력이 강화된다면 전세사기 피해를 줄일 수 있을 것이라 기대된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.434-435
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• 2024

가상자산은 온라인상에서의 투명성과 익명성을 통해 금융서비스 및 전자상거래 발전의 핵심으로 주목받아왔으나, 다크웹에서 사기(Scam) 및 랜섬웨어 등을 통한 자산 탈취의 대상이 되고 있다. 공격자는 익명성을 높이는 자금세탁 기법을 활용하여 탈취한 가상자산의 추적을 우회하며, 이로 인해 피해자에게 정상적인 피해보상이 어려운 실정이다. 본 연구에서는 가상자산 사기 주소에 대한 탈취를 목적으로 한 공격자의 사기 유형을 파악하고, 피해를 최소화하기 위해 대표적인 가상자산 피해 신고 사이트 Chainabuse의 사기 주소에 대한 Top Scammer 주소 수집 및 사기 동향 분석이 가능한 시스템을 제안한다.

• Steel and Composite Structures
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• v.52 no.2
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• pp.237-248
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• 2024

In order to make the dynamic analysis and design of improved composite beam with corrugated steel web (CBGSCC) bridge more efficient and economical, the parametric self-cyclic analysis model (SCAM) was written in Python on Anaconda platform. The SCAM can call ABAQUS finite element software to realize automatic modeling and dynamic analysis. For the CBGSCC bridge, parameters were set according to the general value range of CBGSCC bridge parameters in actual engineering, the SCAM was used to calculate the large sample model generated by parameter coupling, the optimal value range of each parameter was determined, and the sensitivity of the parameters was analyzed. The number of diaphragms effects weakly on the dynamic characteristics. The deck thickness has the greatest influence on frequency, which decreases as the deck thickness increases, and the deck thickness should be 20-25 cm. The vibration frequency increases with the increase of the bottom plate thickness, the web thickness, and the web height, the bottom plate thickness should be 17-23mm, the web thickness should be 13-17 mm, and the web height should be 1.65-1.7 5 m. Web inclination and Skew Angle should not exceed 30°, and the number of diaphragms should be 3-5 pieces. This method can be used as a new method for structural dynamic analysis, and the importance degree and optimal value range of each parameter of CBGSCC bridge can be used as a reference in the design process.

• Journal of Industrial Convergence
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• v.19 no.6
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• pp.37-47
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• 2021

Today, people share information and communicate with others using various information and communication media such as e-mail, smartphones, SNS, etc. However, it is being used in malicious attacks to send a large amount of illegal spam or to use it for fraud by using illegally collected personal information and devices that are vulnerable to security. Illegal spam, smishing, and fraudulent mail(SCAM) cause a lot of direct and indirect damage to companies and users, including not only social costs such as mental fatigue, but also unnecessary consumption of IT infrastructure resources and economic losses. Although there are regulations related to spam, violators of the law are still on the rise by circumventing the law, and victims are constantly occurring, so it is necessary to review what the problem is. This study examined domestic and foreign spam-related regulations and spam-related response activities, identified problems, and suggested improvement countermeasures. Through this study, it was intended to suggest directions for improving spam-related systems in order to block illegal spam and prevent fraudulent damage.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.5
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• pp.165-170
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• 2023

With the recent rise of blockchain technology, cryptocurrency platforms using it are increasing, and currency transactions are being actively conducted. However, crimes that abuse the characteristics of cryptocurrency are also increasing, which is a problem. In particular, phishing scams account for more than a majority of Ethereum cybercrime and are considered a major security threat. Therefore, effective phishing scams detection methods are urgently needed. However, it is difficult to provide sufficient data for supervised learning due to the problem of data imbalance caused by the lack of phishing addresses labeled in the Ethereum participating account address. To address this, this paper proposes a phishing scams detection method that uses both Trans2vec, an effective graph embedding techique considering Ethereum transaction networks, and semi-supervised learning model Tri-training to make the most of not only labeled data but also unlabeled data.