• Journal of Information Processing Systems
• /
• v.20 no.3
• /
• pp.391-398
• /
• 2024

Given the further promotion of economic globalization, China's financial market has also expanded. However, at present, this market faces substantial risks. The main financial and economic risks in China are in the areas of policy, credit, exchange rates, accounting, and interest rates. The current status of China's financial market is as follows: insufficient attention from upper management; insufficient innovation in the development of the financial economy; and lack of a sound financial and economic risk protection system. To further understand the current situation of China's financial market, we conducted a questionnaire survey on the financial market and reached the following conclusions. A comprehensive enterprise questionnaire from the government's perspective, the enterprise's perspective and the individual's perspective showed that the following problems exist in the financial and economic risk prevention aspects of big data and Internet of Things in China. The political system at the country's grassroots level is not comprehensive enough. The legal regulatory system is not comprehensive enough, leading to serious incidents of loan fraud. The top management of enterprises does not pay enough attention to financial risk prevention. Therefore, we constructed a financial and economic risk prevention model based on big data and Internet of Things that has effective preventive capabilities for both enterprises and individuals. The concept reflected in the model is to obtain data through Internet of Things, use big data for screening, and then pass these data to the big data analysis system at the grassroots level for analysis. The data initially screened as big data are analyzed in depth, and we obtain the original data that can be used to make decisions. Finally, we put forward the corresponding opinions, and their main contents represent the following points: the key is to build a sound national financial and economic risk prevention and assessment system, the guarantee is to strengthen the supervision of national financial risks, and the purpose is to promote the marketization of financial interest rates.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.25 no.1
• /
• pp.133-146
• /
• 2015

Ever sophisticated e-finance fraud techniques have led to an increasing number of reported phishing incidents. Financial authorities, in response, have recommended that we enhance existing Fraud Detection Systems (FDS) of banks and other financial institutions. FDSs are systems designed to prevent e-finance accidents through real-time access and validity checks on client transactions. The effectiveness of an FDS depends largely on how fast it can analyze and detect abnormalities in large amounts of customer transaction data. In this study we detect fraudulent transaction patterns and establish detection rules through e-finance accident data analyses. Abnormalities are flagged by comparing individual client transaction patterns with client profiles, using the ruleset. We propose an effective flagging method that uses decision trees to normalize detection rules. In demonstration, we extracted customer usage patterns, customer profile informations and detection rules from the e-finance accident data of an actual domestic(Korean) bank. We then compared the results of our decision tree-normalized detection rules with the results of a sequential detection and confirmed the efficiency of our methods.

• Korean Security Journal
• /
• no.62
• /
• pp.185-203
• /
• 2020

While overall crime has been on the decline since 2009, voice phishing has rather been on the rise. The government and academia have presented various measures and conducted research to eradicate it, but it is not enough to catch up with evolving voice phishing. In the study, researchers focused on catching criminals and preventing damage from voice phishing, which is difficult to recover from. In particular, a voice phishing prediction method using the Fraud Detection System (FDS), which is being used to detect financial fraud, was studied based on the fact that the victim engaged in financial transaction activities (such as account transfers). As a result, it was conceptually derived to combine big data such as call details, messenger details, abnormal accounts, voice phishing type and 112 report related to voice phishing in machine learning-based Fraud Detection System(FDS). In this study, the research focused mainly on government measures and literature research on the use of big data. However, limitations in data collection and security concerns in FDS have not provided a specific model. However, it is meaningful that the concept of voice phishing responses that converge FDS with the types of data needed for machine learning was presented for the first time in the absence of prior research. Based on this research, it is hoped that 'Voice Phishing Damage Prediction System' will be developed to prevent damage from voice phishing.

• The Journal of the Convergence on Culture Technology
• /
• v.4 no.1
• /
• pp.193-200
• /
• 2018

This study is an experiential case study of cybercrime fraud that combines pharming and voice phishing in April 2017. Research on victims who have actually suffered in the study of crime or disaster is a very useful field in establishing crime prevention measures. This study is significant in that Korea is relatively poor in this kind of research. I got cyber fraud as a consequence of my loss of reasonable judgment due to mental confusion when a companion dog who was raised for 8 years was in a very dangerous situation with cystitis. Fortunately, I received all the damages in a quick report, but the period was eight months. It took too much time to get back all the damages, so I had to suffer another pain. Based on my experience, I suggest damage prevention measures. First, when a certain condition and a certain amount are transferred, the transaction is automatically stopped or a more strict confirmation procedure is added. Secondly, trafficking means to arrest the perpetrator without any harm to the victim is sought. Third, the victims of crime should be promptly reimbursed for damages or a system for lending their living funds to zero or lower interest rate.

• The Journal of Industrial Distribution & Business
• /
• v.12 no.12
• /
• pp.1-10
• /
• 2021

Purpose: Cyber criminals have affected various markets and the banking system has encountered various kinds of cyberattacks. The purpose of this study is to analyze cybercrime that is an emerging threat and investigate the significant contribution of financial literacy and public awareness on cybercrimes. To understand the security issues and the need for corrective steps, the techniques and strategies used by cyber fraudsters in obtaining unauthorized access and use the financial information for purpose of fraud need to be understood. Research design, data and methodology: A sample of 123 banks employees from 12 commercial banks in Malaysia was surveyed. This study differs from previous studies as it surveyed the employees' awareness, and this approach fills in the gap in existing literature. Results: The financial literacy and public awareness have positive impact on organizational performance effectiveness to combat threat of cybercrime. Some recommendations are also proposed from research findings, for banking industry and government regulations. Conclusion: The present study focuses on banking sector so its findings cannot be generalized to other sectors. Linking these topics has created a new study in combating threat of cybercrimes generally, and specifically in Malaysia. The present study enhances the understanding of customers' role to combat the impact of cybercrimes on performances of banking industry.

• Proceedings of the CALSEC Conference
• /
• 2002.01a
• /
• pp.238-241
• /
• 2002

·전자상거래: 서로 보지 않고 하는 거래 온라인 범죄(Online Fraud)급증 90％ of information security managers have detected breaches at their organizations within a year 74％ of companies have experienced financial losses because of cybercrime price tag on e-security breaches:>$17 billion worldwide in 2000(source: CIO Magazine, March 2001) ·전자상거래 최대의 걸림돌: 신뢰 62％ cited trust as the top E-commerce barrier -Authentication was key to 60％: Privacy was key to 56％ ·(1999 ITAA and E＆Y Survey) 인터넷을 신뢰의 공간(Trust Network)으로 만들자. (OECD의 Global Theme. 1998.10) 전자상거래 신뢰 확보→인증기관 출현(중략)

• The Journal of Society for e-Business Studies
• /
• v.23 no.4
• /
• pp.153-169
• /
• 2018

Previous e-financial anomalies analysis and detection technology collects large amounts of electronic financial transaction logs generated from electronic financial business systems into big-data-based storage space. And it detects abnormal transactions in real time using detection rules that analyze transaction pattern profiling of existing customers and various accident transactions. However, deep analysis such as attempts to access e-finance by insiders of financial institutions with large scale of damages and social ripple effects and stealing important information from e-financial users through bypass of internal control environments is not conducted. This paper analyzes the management status of e-financial security programs of financial companies and draws the possibility that they are allies in security control of insiders who exploit vulnerability in management. In order to efficiently respond to this problem, it will present a comprehensive e-financial security management environment linked to insider threat monitoring as well as the existing e-financial transaction detection system.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2000.10a
• /
• pp.277-280
• /
• 2000

Credit evaluation is one of the most important and difficult tasks fur credit card companies, mortgage companies, banks and other financial institutes. Incorrect credit judgement causes huge financial losses. This work describes the use of an evolutionary-fuzzy system capable of classifying suspicious and non-suspicious credit card transactions. The paper starts with the details of the system used in this work. A series of experiments are described, showing that the complete system is capable of attaining good accuracy and intelligibility levels for real data.

• The Journal of the Convergence on Culture Technology
• /
• v.3 no.2
• /
• pp.37-42
• /
• 2017

An internet primary bank, which is formed by internet and banks combined, is called the essence of fin-tech, and is currently experiencing rapid growth. 'K-Bank' and 'Kakao Bank', the representative internet primary banks this year, received positive responses as the origin of financial revolution. internet primary banks provide convenient financial services, benefits in time and money for customers. Not long ago, however, undesirable fraud cases caused by a used commodity dealer have happened. The damage exceeds 20,000,000 won. It is because the newborn banks are unable to check the fraud history through the bank account. In this paper, We will analyze the trend in internet primary banks, offer damages and examples, in addition, prevention of damage, and strategies for development.

• Journal of Digital Contents Society
• /
• v.19 no.1
• /
• pp.193-198
• /
• 2018

In Korea, the penetration rate of Internet, telephone and smart devices is reaching the highest level in the world. Cyber financial crimes that exploit such infrastructures continue to evolve. Since the first Voice Phishing crime in May 2006, ten years later, there has been a constant occurrence of Voice Phishing crime. Voice Phishing is a crime in which a victim is phoned for false information to figure out the victim's account number and password. This method of Voice Phishing evolves day by day, and it is difficult to investigate. Most of Voice Phishing is a form of international organized crime that is based in Southeast Asia such as China, and it is not easy to eradicate by international cooperation investigation. The purpose of this study is to investigate the actual situation and case analysis of Voice Phishing crime, and to propose the countermeasures against police Voice Phishing counterplan.