• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.270-281
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• 2021

With the development of information technology, the size of insurance fraud is increasing rapidly every year, and the method is being organized and advanced in conspiracy. Although various forms of prediction models are being studied to predict and detect this, insurance-related information is highly sensitive, which poses a high risk of sharing and access and has many legal or technical constraints. In this paper, we propose a machine learning insurance fraud prediction model based on blockchain, one of the most popular technologies with the recent advent of the Fourth Industrial Revolution. We utilize blockchain technology to realize a safe and trusted insurance information sharing system, apply the theory of social relationship analysis for more efficient and accurate fraud prediction, and propose machine learning fraud prediction patterns in four stages. Claims with high probability of fraud have the effect of being detected at a higher prediction rate at an earlier stage, and claims with low probability are applied differentially for post-reference management. The core mechanism of the proposed model has been verified by constructing an Ethereum local network, requiring more sophisticated performance evaluations in the future.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.908-915
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• 2023

Purpose: The purpose of this study is to examine the types of fraudulent crimes among various crimes taking place during NFT transactions, and to approach institutional problems caused by crime types analysis and crackdown methods and legal limitations. Method: IIn order to classify the types of fraudulent crimes that appear in NFT transactions, the crime types were analyzed through the results of previous studies and cases of current incidents. Result: Most of the crimes that are taking place through NFTs are various types of fraudulent crimes such as rug pools, thefts, personal information theft fraud, and pig murder. Therefore, these types were classified and various damage cases were also analyzed. It is a matter of copyright. Conclusion: Currently, the financial problems caused by the occurrence of fraudulent crimes in NFTs worldwide are the most worrisome, and the scale will be even greater as the market grows in the future. Therefore, in Korea, various institutional supplements and policies should be prepared through analysis of crime types that can affect crime prevention and investigation and arrest activities.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.173-180
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• 2024

Along with its importance, the real estate market poses risks of various fraudulent activities. Recently, a surge in real estate-related scams, such as lease fraud, has caused great financial damage to many ordinary people. These problems are often caused by the complexity of real estate transactions and information imbalance. Therefore, there is an urgent need to secure reliability and improve transparency in the transaction process. In this paper, to solve this real estate fraud problem, we propose a chatbot system using digital technology and artificial intelligence, especially GPT (Generative Pre-Trained Transformer). This system serves to protect users from fraud by providing them with precautions and confirmations in the lease transaction process. In addition, GPT-based chatbots respond to questions from users in time, contributing to reducing uncertainty in the transaction process and increasing reliability.

• Journal of Legislation Research
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• no.53
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• pp.553-591
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• 2017

This article discussed whether so-called 'foreign judgments obtained by fraud' is in breach of public policy provided in Article 217(1)(3) of Civil Procedure Act and, if so, what the specific requirements could be. The summary of the conclusion is as follows. The 'foreign judgments obtained by fraud' is against the municipal procedural public policy and then shall not be recognized. In this regard one more question comes up whether reviewing if 'foreign judgments obtained by fraud' is in breach of the municipal procedural public policy is allowed in consideration of the principle of prohibition of $r{\acute{e}}vision$ au fond. Since the principle is applied entirely in the course of the above reviewing, it is allowed only when it does not breach the principle. The two instances that the reviewing is allowed are where the defendant was not able to produce evidences of fraud during foreign procedures and where the defendant's claim of fraud without evidences was rejected by the foreign court and then evidences of fraud were found after the foreign procedure was completed. On the other hand, the specific requirements for 'foreign judgments obtained by fraud' to be against public policy are following four requirements based on principle of strict interpretation of public policy. (1) plaintiff's intention to fraud, (2) preventing the defendant from being involved in the procedure by fraud or cheating the foreign court using manipulated evidences, (3) the defendant could not present himself in the foreign court procedure due to the plaintiff's extraneous fraud or the foreign court decided wrongly due to intrinsic fraud, and (4) defendant's fundamental procedural rights were breached to the extent that recognizing the effect of foreign judgments was against justice defendant's fundamental procedural rights. These results differ from the Supreme Court 2004. 10. 28. ruling 2002da74213 in many aspects. Most of all, in my opinion there is no need to distinguish between intrinsic fraud and extraneous fraud and reviewing 'foreign judgments obtained by fraud' is not in conflict with the principle of prohibition of $r{\acute{e}}vision$ au fond but the both may coexist. In this regard I expect the variation of the Supreme Court's position and hope to contribute to academia and practitioners.

• Journal of Agricultural Extension & Community Development
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• v.2 no.2
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• pp.235-238
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• 1995

• Korean Security Journal
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• no.9
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• pp.155-176
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• 2005

This study is focused on the job condition, the morale and the job leave of the private security. The private security industry in korea has been grown rapidly in its quantity, but the quality is not followed with it. So The reality on the private security Industry is in the low income and the negative morale, and it leads to leave the job openly. The job leave and the morale of the private security depend on the given job condition. Therefore to improve their job satisfaction and job condition the related parties should have concerned the quality for them. Because the output of their job performance depends on the private security's job morale, In this point of view the morale in the job and job leave have very relationship. The survey on the job condition, the morale and the job leave of the private security has the followings; 1) The male is more unsatisfied than the female in their job condition, and the female is more satisfied than the male in their income. 2) The male is more higher than the female in job leave intention, especially 20s are most higher and 40s are most less. 3) The positive morale in the private security would be grown if the income and job satisfaction would be made in certain level and the fair promotion would be promised. 4) To improve the stability and effectiveness in the private security system the rate of job leave should be reduced and the proper job would be distributed.

• Information Systems Review
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• v.23 no.4
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• pp.45-67
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• 2021

As the transaction volume of the C2C second-hand market is growing, the number of frauds, which intend to earn unfair gains by sending products different from specified ones or not sending them to buyers, is also increasing. This study explores the model that can identify frauds in the online C2C second-hand market by examining the postings for transactions. For this goal, this study collected 145,536 field data from actual C2C second-hand market. Then, the model is built with the characteristics from postings such as the topic and the linguistic characteristics of the product description, and the characteristics of products, postings, sellers, and transactions. The constructed model is then trained by the machine learning algorithm XGBoost. The final analysis results show that fraudulent postings have less information, which is also less specific, fewer nouns and images, a higher ratio of the number and white space, and a shorter length than genuine postings do. Also, while the genuine postings are focused on the product information for nouns, delivery information for verbs, and actions for adjectives, the fraudulent postings did not show those characteristics. This study shows that the various features can be extracted from postings written in C2C second-hand transactions and be used to construct an effective model for frauds. The proposed model can be also considered and applied for the other C2C platforms. Overall, the model proposed in this study can be expected to have positive effects on suppressing and preventing fraudulent behavior in online C2C markets.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.545-551
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• 2005

The main objective of fraud detection is to minimize costs or losses that are incurred due to fraudulent transactions. Because of the problem's nature such as highly skewed, overlapping class distribution and non-uniform misclassification costs, it is, however, practically difficult to generate a classifier that is near-optimal in terms of classification costs at a desired operating range of rejection rates. This paper defines a performance measure that reflects classifier's costs at a specific operating range and offers a cost-sensitive learning approach that enables us to train classifiers suitable for real-world credit card fraud detection by directly optimizing the performance measure with evolutionary programming. The experimental results demonstrate that the proposed approach provides an effective way of training cost-sensitive classifiers for successful fraud detection, compared to other training methods.

• Smart Media Journal
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• v.12 no.2
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• pp.36-41
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• 2023

With the advent of applicant tracking systems, online recruitment has become more popular, and recruitment fraud has become a serious problem. This research aims to develop a reliable model to detect recruitment fraud in online recruitment environments to reduce cost losses and enhance privacy. The main contribution of this paper is to provide an automated methodology that leverages insights gained from exploratory analysis of data to distinguish which job postings are fraudulent and which are legitimate. Using EMSCAD, a recruitment fraud dataset provided by Kaggle, we trained and evaluated various single-classifier and ensemble-classifier-based machine learning models, and found that the ensemble classifier, the random forest classifier, performed best with an accuracy of 98.67% and an F1 score of 0.81.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.69-72
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• 2012

최근 인터넷의 스마트폰 애플리케이션 개발을 통해 사용자들에게 편리한 위치기반 서비스, 증강현실 시스템이 소개되고 있다. 최근 보이스피싱 등의 전화사기 행위가 사회적 문제로 부각되고 있다. 부동산거래 사기에 의한 피해 역시 지속적으로 발생하고 있으며(대법원93다2629,2636 등), 매매과정에서 착오/과실에 의한 부동산 거래 소송(대법원92다38881, 2000다12259 등)역시 지속적으로 발생하고 있다. 부동산 거래현장에서 실시간으로 부동산 등기내역, 실거래가, 공시가격, 거래내역, 개발계획 등의 공공정보를 제공하는 스마트폰 애플리케이션 개발한다. 즉, 증강현실, GPS에 근거한 정확한 위치 및 물건에 대한 정보를 확인할 수 있으므로, 사기/착오/과실/부주의에 의한 부동산 거래를 방지한다. 결과적으로, 부동산 사기로 인한 소송 등 불필요한 사회적 비용을 획기적으로 절감할 수 있는 장점이 있다. 뿐만 아니라, 부동산 실수요자 거래활성화를 유도하는 정부정책에 부합 건전하고 정확한 부동산 거래 활성화에 기여할 것이다.