• Proceedings of the Korea Information Processing Society Conference
• /
• 2009.11a
• /
• pp.635-636
• /
• 2009

공개키 암호 시스템을 이용하는 공인인증서는 IT 기술의 발달과 함께 e-Banking, e-Commerce, e-Finance 등 다양한 분야에서 사용자 인증을 제공하는 수단으로 사용되고 있다. 그러나 최근에 다양한 해킹툴과 사용자 PC의 취약점을 이용하여 PC에 저장된 공인인증서가 유출되는 사고가 발생하면서 전자금융에 대한 안전성을 위협받고 있다. 따라서 본 논문에서는 기존에 공인인증서를 하드디스크에 저장하여 발생하였던 문제점을 해결하고자 모바일 디바이스를 이용하여 전자서명을 수행하는 MobiSign의 공인인증서 이동방식 및 전자서명 방식을 분석한다. 또한 모바일 환경에서 악성코드에 의해서 발생할 수 있는 MobiSign 서비스의 보안 위협을 분석한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2021.11a
• /
• pp.1253-1256
• /
• 2021

떠오르는 ESG 펀드(ETF·ELF)에 투자하는 서비스로 행동하는 소비자가 적극적인 ESG 펀드 기업의 사회적 변화를 주도록 변화를 만들어갈 수 있도록 핀테크와 ESG 플랫폼 통합서비스를 제시한다. 행동하는 소비자들은 증권사가 투자/운용하는 ESG 펀드(ETF·ELF)에 투자하고, 증권사는 발생하는 이익 일부를 사회 취약계층에 기부하여 사회적 책임을 다하는 기업으로 이미지 제고와 증권사 고객 증가, 펀드 자금 증가, 투자받는 기업들은 ESG 경영을 위한 자금 확보를 통해, 소비자와 증권사 그리고 ESG 경영 기업으로 이루어진 선한 영향력의 사이클을 선순환하는 비즈니스 모델과 아키텍쳐를 제시한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2021.11a
• /
• pp.1047-1050
• /
• 2021

코로나19의 영향으로 발열 측정의 중요성은 매우 높아졌다. 현재 이용되고 있는 발열 측정 기기는 사람의 능동적 측정이 요구된다. 본 연구에서 개발된 SDTMBOT은 강화학습기반의 자율 주행과, 딥러닝 기반의 발열 측정 기능을 통하여 특정 장소에 국한되지 않고 넓은 공간에서 자율적이고 지속적인 발열 측정이 가능하다. 이는 기존 사용되고 있는 측정방식과 다른 새로운 방식이며 다가올 With 코로나 시대의 방역에 대한 새로운 시각을 제시한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2022.11a
• /
• pp.794-796
• /
• 2022

본 논문은 에어컨 토출구 살균조명용 UV-LED 에 관한 연구이다. 서론에서는 에어컨 토출구에 증식하는 곰팡이의 문제점과 원인에 대해 조사 분석함으로써 연구의 목적을 설명하였다. 본론에서는 내부를 살균하며 동시에 무드조명의 역할을 수행함으로써 얻을 수 있는 장점과 작동방식에 대하여 설명하고, 가능성을 확인하기 위한 실험을 계획하였다. 실험계획과 실험결과에서는 이전 다른 실험과의 차이점과 실험계획을 설명하고, 실험결과에 대해 설명하며 이번 실험에서의 한계점 및 보안할 점도 함께 설명하였다. UV-LED 의 설치 위치를 예시를 들며 설명하였다. 결론에서는 본 논문에서 설명한 연구의 내용을 종합하고, 향후 연구의 진행방향과 추가적으로 필요한 실험 및 적절한 UV-LED 의 파장선택에 대해서 기술하였다.

• Journal of Digital Convergence
• /
• v.13 no.1
• /
• pp.111-124
• /
• 2015

The economic growth in China takes the step of the Internet/Mobile revolution together. The high internet penetration provided the opportunity to increase the e-commerce market with fast speed. However, due to imbalance of the growth speed and preparation, the problems on various infrastructures and regulations were generated. Therefore, this study investigateed the current status of e-commerce market and sub-categories. This study also discussed about the problem of e-commerce logistics system, consumer protection, R&D investment, and human resources and provided the considerations for the future improvement. Finally, this study diagnosed the mobile payment and internet finance market and new e-commerce tax regulation, and then suggested institutional implications for the international standardization. This study is meaningful to provide the first implication to the Korean exporters after Chinese government had announced market open strategy for the 5 year e-commerce development plan.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.11 no.5
• /
• pp.550-555
• /
• 2018

This study aims to identify and compare contents and keywords used in articles related to blockchain applications to various industries. The text mining and Semantic Network Analysis, as methods of keyword network analysis, were used to analyze articles including terms of 'finance' 'energy' and 'logistics', which media and government frequently mentioned as areas that can apply blockchain technologies. For this study, data were collected from 43,093 articles from January, 2017 through July, 2018. Data crawling was carried out by using Python BeautifulSoup and data cleaning was performed in order to eliminate mutual redundancies of the three terms. After that, text mining and semantic network analysis were performed using Textom and UCInet for network analysis between keywords. The results showed that all the three terms were similar in terms of 'technology', but there were differences in the contents of 'government policy' or 'industry' issues. In addition, there were differences in frequencies and centralities of these terms.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.1
• /
• pp.149-164
• /
• 2019

Digital Transformation and the Fourth Industrial Revolution, electronic financial services should be provided safely in accordance with rapidly changing technology changes in the times of change. However, telecommunication finance fraud (voice phishing) accidents are currently ongoing, and various efforts are being made to eradicate accidents such as legal amendment and improvement of policy system in order to cope with continuous increase, intelligence and advancement of accidents. In addition, financial institutions are trying to prevent fraudulent accidents by improving and upgrading the abnormal financial transaction detection system, but the results are not very clear. Despite these efforts, telecommunications and financial fraud incidents have evolved to evolve against countermeasures. In this paper, we propose an intelligent over - the - counter financial transaction system modeled through scenario - based Rule model and artificial intelligence algorithm to prevent financial transaction accidents by voice phishing. We propose an implementation model of artificial intelligence abnormal financial transaction detection system and an optimized countermeasure model that can block and respond to analysis and detection results.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.20 no.6
• /
• pp.67-81
• /
• 2010

As wide propagation of smartphones, e-commerce with smartphones increases rapidly. Such as transfer or stock trade systems. It has prospect that most of financial companies going to offer e-commerce systems via smartphones. And e-commerce via smartphones will be increased, hence the nature of smartphone that can be used whenever, wherever. However, legislation of e-commerce in Korea does not reflect these characteristics of smartphones, because it has set standards in regular PC. So that this study is security threat and feature of smartphones considering that the current legal system will use Certificate constraints, ensuring the safety of e-commerce and install security programs for protection of users, e-commerce responsible for the accident analysis has focused on the issues presented for this improvement.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.6
• /
• pp.9-19
• /
• 2016

In finance literature, stock liquidity showing how stocks can be cashed out in the market has received rich attentions from both academicians and practitioners. The reasons are plenty. First, it is known that stock liquidity affects significantly asset pricing. Second, macroeconomic announcements influence liquidity in the stock market. Therefore, stock liquidity itself affects investors' decision and managers' decision as well. Though there exist a great deal of literature about stock liquidity in finance literature, it is quite clear that there are no studies attempting to investigate the stock liquidity issue as one of decision making problems. In finance literature, most of stock liquidity studies had dealt with limited views such as how much it influences stock price, which variables are associated with describing the stock liquidity significantly, etc. However, this paper posits that stock liquidity issue may become a serious decision-making problem, and then be handled by using data mining techniques to estimate its future extent with statistical validity. In this sense, we collected financial data set from a number of manufacturing companies listed in KRX (Korea Exchange) during the period of 2010 to 2013. The reason why we selected dataset from 2010 was to avoid the after-shocks of financial crisis that occurred in 2008. We used Fn-GuidPro system to gather total 5,700 financial data set. Stock liquidity measure was computed by the procedures proposed by Amihud (2002) which is known to show best metrics for showing relationship with daily return. We applied five data mining techniques (or classifiers) such as Bayesian network, support vector machine (SVM), decision tree, neural network, and ensemble method. Bayesian networks include GBN (General Bayesian Network), NBN (Naive BN), TAN (Tree Augmented NBN). Decision tree uses CART and C4.5. Regression result was used as a benchmarking performance. Ensemble method uses two types-integration of two classifiers, and three classifiers. Ensemble method is based on voting for the sake of integrating classifiers. Among the single classifiers, CART showed best performance with 48.2%, compared with 37.18% by regression. Among the ensemble methods, the result from integrating TAN, CART, and SVM was best with 49.25%. Through the additional analysis in individual industries, those relatively stabilized industries like electronic appliances, wholesale & retailing, woods, leather-bags-shoes showed better performance over 50%.

• Information Systems Review
• /
• v.22 no.1
• /
• pp.59-72
• /
• 2020

Artificial Intelligence is establishing itself as a familiar tool from an intractable concept. In this trend, financial sector is also looking to improve the problem of existing system which includes Fraud Detection System (FDS). It is being difficult to detect sophisticated cyber financial fraud using original rule-based FDS. This is because diversification of payment environment and increasing number of electronic financial transactions has been emerged. In order to overcome present FDS, this paper suggests 3 types of artificial intelligence models, Generative Adversarial Network (GAN), Deep Neural Network (DNN), and Convolutional Neural Network (CNN). GAN proves how data imbalance problem can be developed while DNN and CNN show how abnormal financial trading patterns can be precisely detected. In conclusion, among the experiments on this paper, WGAN has the highest improvement effects on data imbalance problem. DNN model reflects more effects on fraud classification comparatively.