• Journal of the Korea Society of Computer and Information
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• v.20 no.9
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• pp.137-145
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• 2015

The Criminal Law of South Korea has needed to cope with new kinds of crimes such as the fraud by use of computer efficiently in a legislative way because the society has witnessed the rapid progress of the industrialization and informatization after established in 1953. As a result, the Criminal Law revised on December 29, 1995, created the regulations of the crimes related to fraud by use of computer, work disturbance, and secret piracy by using information processing units. The regulation stipulated in Clause 347, Article 2 of Criminal Law is the most typical one against the new crimes. However, the new regulation of fraud by use of computer, established and revised to supplement the lacking parts of the current rules of the punishment of fraud, limits its object to "any benefits to property." not to "property" itself, and so cannot achieve the purpose of the revision of the law. This paper aims to suggest a new legislative measure about the object of the regulation of fraud by use of computer to solve this kind of problem efficiently.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.31-40
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• 2021

The increasing number of credit card fraud cases has become a considerable problem since the past decades. This phenomenon is due to the expansion of new technologies, including the increased popularity and volume of online banking transactions and e-commerce. In order to address the problem of credit card fraud detection, a rule-based approach has been widely utilized to detect and guard against fraudulent activities. However, it requires huge computational power and high complexity in defining and building the rule base for pattern matching, in order to precisely identifying the fraud patterns. In addition, it does not come with intelligence and ability in predicting or analysing transaction data in looking for new fraud patterns and strategies. As such, Data Mining and Machine Learning algorithms are proposed to overcome the shortcomings in this paper. The aim of this paper is to highlight the important techniques and methodologies that are employed in fraud detection, while at the same time focusing on the existing literature. Methods such as Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), naïve Bayesian, k-Nearest Neighbour (k-NN), Decision Tree and Frequent Pattern Mining algorithms are reviewed and evaluated for their performance in detecting fraudulent transaction.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.49
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• pp.139-164
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• 2011

Traditionally courts have been adopted over the years two standards of dealing with compliance of documents such as strict compliance and substantial compliance and the substantial compliance, which was somewhat less demanding than the strict compliance. However the new guidelines of ICC's international standard banking practice for the examination of documents under documentary credits set up how the UCP is to be applied in practice. The payment obligations of an issuing bank to a beneficiary are independence of the performance or the nonperformance of any contract underlying the letter of credit. However, strictly applying the principle of independence and abstraction could produce unfair results by operating unjustly enrich an unscrupulous beneficiary in case of fraud. Accordingly, when a beneficiary presents complying documents, the issuing bank is bound to honour the presentation unless the fraud rule applies on the facts of the case such as forged or material fraud. If it does, the issuing bank(issuer) needs not pay despite the complying presentation of documents by the beneficiary under the Uniform Commercial Code Article 5-109 and case law in America. However the fraud rule was not addressed in UCP 600. In conclusion, view in terms of legal principle and the court cases is variable and difficult to honour or dishonour the presentation in case of application of the independence principle and fraud rule such as the problems on burden of proof timely, possibility of granting injunction in order to protect against victim for bona fide applicant.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.11
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• pp.660-674
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• 2014

RFID system has been used in a variety of services. So, a lot of attacks like a free ride on the service, leakage of property or personal information are known. Therefore, the solutions that address these attacks have been proposed. Among the attacks, mafia fraud, a kind of relay attack, can not be addressed by common authentication protocol. So, Hancke and Kuhn used distance bounding protocol for RFID authentication. After that, Munilla and Peinado modified HK protocol by adding void challenge. So the mafia fraud success probability of adversary is lower than probability of HK protocol. Ahn et al. proposed a protocol that reduces number of a hash computation and traffic than MP protocol. Here, we show that MP protocol can not defend the terrorist fraud and is vulnerable to noise. And we show that also AYBN protocol is vulnerable to mafia fraud and key leakage. Moreover, we propose a new protocol and our experimental results show that our protocol is secure to terrorist and mafia fraud.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.263-267
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• 2005

Building classifiers for financial real-world classification problems is often plagued by severely overlapping and highly skewed class distribution. New performance measures such as receiver operating characteristic (ROC) curve and area under ROC curve (AUC) have been recently introduced in evaluating and building classifiers for those kind of problems. They are, however, in-effective to evaluation of classifier's discrimination performance in a particular class of the classification problems that interests lie in only a local operating range of the classifier, In this paper, a new method is proposed that enables us to directly improve classifier's discrimination performance at a desired local operating range by defining and optimizing a partial area under ROC curve or domain-specific curve, which is difficult to achieve with conventional classification accuracy based learning methods. The effectiveness of the proposed approach is demonstrated in terms of fraud detection capability in a real-world fraud detection problem compared with the MSE-based approach.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.529-536
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• 2023

The secondhand market in Korea has been showing steady growth. However, the number of fraud cases and the amount of damages from fraudulent activities in secondhand transactions are also increasing. As of 2021, the size of the secondhand market reached 24 trillion won, but the total amount of fraud-related damages reached 360.6 billion won. In order to prevent fraud between individuals, secondhand trading platforms have implemented a safety payment system. However, new types of fraud methods exploiting the safety payment system have emerged, undermining the security of secondhand transaction safety payments. In this study, we aim to utilize text mining to examine the current state of the safety payment system in secondhand transactions and propose improvement measures by analyzing the system through text mining and network analysis.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.5
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• pp.1179-1195
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• 2018

Recently, a variety of attacks on web services have been occurring through a multiple access environment such as PC, tablet, and smartphone. These attacks are causing various subsequent damages such as online fraud transactions, takeovers and theft of accounts, fraudulent logins, and information leakage through web service vulnerabilities. Creating a new fake account for Fraud attacks, hijacking accounts, and bypassing IP while using other usernames or email addresses is a relatively easy attack method, but it is not easy to detect and block these attacks. In this paper, we have studied a method to detect online fraud transaction and obsession by identifying and managing devices accessing web service using web-based device fingerprinting. In particular, it has been proposed to identify devices and to manage them by scoring process. In order to secure the validity of the proposed scheme, we analyzed the application cases and proved that they can effectively defend against various attacks because they actively cope with online fraud and obtain visibility of user accounts.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.79-95
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• 2012

As credit loan products significantly increase in most financial institutions, the number of fraudulent transactions is also growing rapidly. Therefore, to manage the financial risks successfully, the financial institutions should reinforce the qualifications for a loan and augment the ability to detect a credit loan fraud proactively. In the process of building a classification model to detect credit loan frauds, utility from classification results (i.e., benefits from correct prediction and costs from incorrect prediction) is more important than the accuracy rate of classification. The objective of this paper is to propose a new approach to building a classification model for detecting credit loan fraud based on an individual-level utility. Experimental results show that the model comes up with higher utility than the fraud detection models which do not take into account the individual-level utility concept. Also, it is shown that the individual-level utility computed by the model is more accurate than the mean-level utility computed by other models, in both opportunity utility and cash flow perspectives. We provide diverse views on the experimental results from both perspectives.

• The KIPS Transactions:PartC
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• v.17C no.4
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• pp.307-314
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• 2010

Recently, it is proved that contactless smart-card based RFID tags, which is used for proximity authentication, are vulnerable to relay attacks with various location-based attacks such as distance fraud, mafia fraud and terrorist fraud attacks. Moreover, distance bounding protocols have been researched to prevent these relay attacks that can measure the message transmitted round-trip time between the reader and the tag. In 2005, Hancke and Kuhn first proposed an RFID distance bounding protocol based on secure hash function. However, the Hancke-Kuhn protocol cannot completely prevent the relay attacks because an adversary has (3/4)$^n$ attack success probability. Thus, this paper proposes a new distance-bounding protocol for light-weight RFID systems that can reduce to (5/8)$^n$ for the adversary's attack success probability. As a result, the proposed protocol not only can provide high-space efficient based on a secure hash function and XOR operation, but also can provide strong security against the relay attacks because the adversary's attack success probability is optimized to (5/8)$^n$.

• Convergence Security Journal
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• v.16 no.5
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• pp.33-40
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• 2016

Credit card is means of payment used like cash in terms of function and its users have increased consistently. With development of Internet and electronic commerce a role as payment method of credit card has been growing. But as the risk which results from centralized information and online increases, credit card fraud is also growing. Card theft and loss are decreasing due to countermeasure of card companies and financial supervisory authorities, while card forge and identity theft are increasing. Recently because of frequent personal information leakage and deregulation of financial security following easy-to-use payment enforcement, customer's anxiety about card fraud is growing. And the increase of card fraud lowers trust on credit system as well as causes social costs. In this paper, the security problems of card operating system are addressed in depth and the measures such as immediate switch to IC card terminals, introduction of new security technology, supervision reinforcement of the authorities are proposed.