Types Of Fraud Research Articles

Detection of Salmonidae ingredient using mini-DNA barcoding in conjunction with a rapid visual inspection method

Using species outside Salmonidae to prepare salmon products has been widely revealed as a new type of fraud in China and other countries with less stringent labeling stipulations, highlighting the necessity to establish proper methods for rapid screening of Salmonidae ingredient. The present work selected mitochondrial Cytb gene as the target, and developed a novel mini-DNA barcoding assay to identify the salmonids ingredient in processed fish products. Results showed that the novel method is highly specific for salmonids detection and only the seven common salmonids species were successfully amplified. With the inclusion of HRM analysis, we can make an accurate differentiation of Salar salar, Oncorhynchus mykiss, and the other wild-caught Oncorhynchus species, which are deep in the scandal of species mislabeling. Moreover, a closed-tube visual detection can also be achieved by the preaddition of HNB (hydroxyl naphthol blue) and SYTO 9 in the reaction mixture, allowing an easy and rapid way to distinguish positive from negative. Finally, the novel assay was successfully applied on commercial products and the absence of salmonids ingredient indicated mislabeling with 4 commercial products. Overall, mini-DNA barcoding is a robust tool for fish species identification and the novel method is effective in screening Salmonidae ingredient.

English

Phishing is a type of online fraud which enables attackers to trick individuals into giving away confidential data like login credentials or financial data. A phishing website utilizes a URL that is comparable to a reasonable website to trick users into thinking it is legitimate, or it may comprise suspicious links or forms which has been developed for collecting sensitive data from users. Machine learning (ML) can be utilized to categorise websites as phishing or legitimate to protect users from falling victim to these attacks. There are several approaches to using machine learning for phishing website classification. This article focuses on the design of Chicken Swarm Optimization with Improved Random Forest for Phishing Website Classification (CSOIRF-PWC) technique. The CSOIRF-PWC technique aims to discriminate the legitimate and phishing websites accurately. To execute this, the presented CSOIRF-PWC approach initially performs the data normalization process. Next, the classification of phishing websites takes place using the IRF classifier. For improving the classification performance of the RF classifier, the parameter tuning process is performed through the CSO algorithm, which supports attaining improved classification performance. The simulation values of the CSOIRF-PWC methodology are investigated on two datasets, and the outputs are investigated under diverse measures. The comprehensive comparative outcomes emphasized the enhanced performance of the CSOIRF-PWC system over other methodologies in terms of several measures.

Fraud in a digital society in the context of social change

The article analyzes the problems of fraud in the modern digital society in the context of social changes caused by both the COVID-19 pandemic and the current geopolitical situation. The authors study in detail the types of financial fraud in this area. They pay special attention to the types of digital fraud: telephone fraud and IP-telephony, SMS fraud, phishing, sniffering (message interception), skimming (theft of card data), which are associated with the emergence of cryptocurrencies. The article presents the data of the authors’ sociological research conducted by the method of an online questionnaire survey (n = 765). The study showed that only 44 % of respondents are sufficiently informed about the types of fraud to protect themselves from modern internet scammers. An analysis of data on certain types of digital fraud showed that 20 % of respondents lost money due to telephone or Internet fraud, 16 % of respondents personally encountered IP telephony, and 40 % have no idea about such a type of fraud as sniffering and existing anti-virus protection against it. The research also showed the vulnerability, first of all, of the male half of the population over 40 years of age in the field of internet fraud. Therefore, public authorities, together with the media, business and other actors of Russian society, need to strengthen the policy in the field of improving the level of financial and digital literacy of the population.

Can digital transformation prohibit corporate fraud? Empirical evidence from China

ABSTRACT The pace of corporate digital transformation has been accelerating all over the world. This paper investigates the impact of digital transformation on corporate fraud with probit model in Chinese scenario. The results show that the digital transformation of enterprises can help curb the occurrence of fraud in general. However, the heterogeneity test results suggest that the application of digital technology may increase the possibility of some types of fraud as well. Considering possible endogeneity issues, this paper checks the results with the methods of Heckman two-step model and IV probit model and the conclusion remains robust. The empirical results suggest that accelerating the digital transformation of enterprises will help improve the quality of enterprises, optimize the capital market environment, but it is very important to guard against delayed disclosure in digitalization era.

How (Not) to Win a Medal: Military Professionalism, Gallantry Awards, and the Problem of Fraud

Gallantry medals are invested with deep significance not only by the armed forces but also by civilian society. In the last decade, there has been a debate in sociology about whether the medallic regime has become post-heroic or whether it has professionalized. This article contributes to these debates by focusing on the topic of fraudulent medals. Fake medals are very rare; there has been one proven case in the United Kingdom in the last 20 years. However, precisely because fake medals are the exception, their pathologies illustrate the processes by which medals are actually awarded with particular clarity. This analysis of the fake medal shows that gallantry awards have professionalized; in the UK medals have become more meritocratic, recognizing skill not status. The awarding process is also more objective. Yet, its very professionalism is ironically vulnerable to a specific type of fraud by skilful but cynical citation writers.

What Do These Tweets Mean for Us? How Analysis of Consumer Tweets Sheds Light on Consumers’ CSR Beliefs and Firm Confidence

Through an experimental design and using the theoretical lens of categorization and cognitive appraisal theories, this research examines how tweets evaluated based on tone (valence and character) coupled with the CSR type (Corporate Operating Performance vs. Corporate Social Performance) and the related CSR fraud can subsequently impact their CSR beliefs and confidence in the firm. CSR beliefs are the extent that an individual feels a firm should be engaging in CSR activities. It was found that the valence of the tweets moderated by the tweet’s character or tone impacts the consumer’s belief in firms engaging in CSR activities. Tweet valence increases confidence in firms while tweet valence moderated by the fraud type (CSP fraud vs. COP fraud) decreases confidence in firms. Negative utilitarian tweets lead to less confidence in firms while positive utilitarian tweets lead to more confidence in firms, which can be explained through cognitive appraisal theory.

Meat food fraud risk in Chinese markets 2012–2021

Food fraud is a major concern worldwide, and the majority of cases include meat adulteration or fraud. Many incidences of food fraud have been identified for meat products both in China and abroad over the last decade. We created a meat food fraud risk database compiled from 1987 pieces of information recorded by official circular information and media reports in China from 2012 to 2021. The data covered livestock, poultry, by-products, and various processed meat products. We conducted a summary analysis of meat food fraud incidents by researching fraud types, regional distribution, adulterants and categories involved, categories and sub-categories of foods, risk links and locations, etc. The findings can be used not only to analyze meat food safety situations and study the burden of food fraud but also help to promote the efficiency of detection and rapid screening, along with improving prevention and regulation of adulteration in the meat supply chain markets.

Forensic as a tool of anti-crisis management and counteraction to offenses in the field of bankruptcy

Introduction. The problems of identifying signs and preventing bankruptcy at enterprises have been investigated. The priority of measures to effectively investigate bankruptcy offenses is justified. The purpose of the paper is to determine the analysis of approaches to understanding the essence of "forensics" as an effective tool for identifying signs and preventing bankruptcy, forming a proper source of evidence for bringing to bankruptcy, promising direction of investigation of complex economic offenses and its delimitation with forensic and economic expertise. Results. The origin of the concept of "forensic" was investigated and its content was defined as independent activities aimed at identifying, analyzing, resolving financial, commercial, legal or other issues; development of procedures aimed at countering and preventing all types of fraud in the economic sphere, in particular, bringing to bankruptcy, identifying the perpetrators. In the course of the comparative analysis of the concept of "forensic" with the category of "judicial economic examination," their general features and differences were determined according to the following criteria: essence, regulatory regulation, tasks, grounds for conducting, subject, object, initiator of conducting, stages, dates of conducting, results, sources of financing. It is justified that the concept of "forensic" is wider than the category of "judicial economic examination," accordingly, judicial economic examination is a component of forensic examination. We have studied the peculiarities and advantages of using a forensic in the anti-crisis management system at the enterprise. It has been determined that the syringe is a tool that is successfully used in foreign practice in developed countries, but has not yet been properly used in Ukraine. On the basis of this, the feasibility of implementing the best practices of foreign countries in the system of anti-crisis management and the introduction of forensic equipment in the domestic system of countering bankruptcy at enterprises and identifying illegal actions in the field of bankruptcy at enterprises is justified. Conclusion. The absence of a proper regulatory field for the use of a penalty was determined and the need to implement measures to legislatively resolve the use of the penalty tools as an innovative tool for anti-crisis management and combating crimes in the field of bankruptcy at enterprises was justified.

Insider employee-led cyber fraud (IECF) in Indian banks: from identification to sustainable mitigation planning

ABSTRACT This paper explores the different insider employee-led cyber frauds (IECF) based on the recent large-scale fraud events of prominent Indian banking institutions. Examining the different types of fraud and appropriate control measures will protect the banking industry from fraudsters. In this study, we identify and classify Cyber Fraud (CF), map the severity of the fraud on a scale of priority, test the mitigation effectiveness, and propose optimal mitigation measures. The identification and classification of CF losses were based on a literature review and focus group discussions with risk and vigilance officers and cyber cell experts. The CF was analyzed using secondary data. We predicted and prioritized CF based on machine learning-derived Random Forest (RF). An efficient fraud mitigation model was developed based on an offender-victim-centric approach. Mitigation is advised both before and after fraud occurs. Through the findings of this research, banks and fraud investigators can prevent CF by detecting it quickly and controlling it on time. This study proposes a structured, sustainable CF mitigation plan that protects banks, employees, regulators, customers, and the economy, thus saving time, resources, and money. Further, these mitigation measures will improve the reputation of the Indian banking industry and ensure its survival.

Tasriyahand legal assessments related to it in Islamic jurisprudence

Tasriyah is a type of fraud in the sale of animals such as sheep, cows, and camels, and the wise legislator forbade this process, which is to leave milking a sheep, cow, or she-camel for several days, and considered it a form of fraud by the seller. She gives him a lot of milk to deceive the buyer with her udder full of milk. Aside from the tap, the jurists considered this to be a defect in which the sphincter is returned, but it is returned with a saa' of dates instead of the milk that was taken from the udder of a sheep or a she-camel, if it becomes apparent to the buyer that it has become, but they did not leave the option to the purchaser open. Some of them stipulated the response within the first three days, and spelled out the response within the first day . In addition to their disagreement over the multiplicity of returning a saa' of dates if there are many misrata, particularly if it was obtained under a single contract.

LITERATURE REVIEW OF AUDIT INVESTIGATION ROLE AND WHISTLEBLOWING SYSTEM IN EFFORTS TO FRAUD DISCLOSURE

Economic developments have a good impact on society but also lead to the development of acts of fraud committed by some people which can pose a threat to an institution or a country. This shows that something needs to be done to combat this type of fraud. This study aims to determine the role of investigative audits and whistleblowing systems in efforts to disclose fraud. The method in this study uses a qualitative approach and this type of research is included in the literature review. There are several steps taken by researchers during the research process, such as selecting data, presenting data, and drawing conclusions. The results of the study show that investigative audits and whistleblowing systems have an important role in efforts to identify and disclose fraud.

Who Became Victims of Financial Frauds during the COVID-19 Pandemic in Japan?

The COVID-19 pandemic has provided a unique opportunity for fraudsters to innovatively swindle money through the trade of necessary goods and services. Although several incidents of financial fraud were reported during the pandemic, there is a lack of studies comparing financial frauds before and during the pandemic and the risk factors associated with frauds. This study uses two waves of a panel survey conducted before and during the pandemic and applies mean comparison tests and logit regressions to investigate financial frauds at the aggregate and specific levels. The comparative analysis shows no significant change in financial frauds at the aggregate level between before and during the pandemic. However, refund frauds for men have increased, while loan guarantee frauds for women have decreased significantly during the pandemic. The regression results show that being male, younger in age, living with family, having employment status, having a household income, household assets, having financial literacy, having a myopic view of the future, and having careful buying habits are associated with the probability of being victims of financial frauds during the pandemic. The study reveals differences in risk factors associated with victims of financial frauds at the aggregate and specific levels. The results further imply that risk factors differ across the types of fraud, which authorities should consider while combating financial frauds.

Consumer Experience of Mistreatment and Fraud in Financial Services: Implications from an Integrative Consumer Vulnerability Framework.

This study utilizes the National Financial Well-Being Survey (NFWS) from the Consumer Financial Protection Bureau (CFPB) to investigate the profiles of American consumers who experience mistreatment or a type of fraud in financial services (compromised accounts). An integrative consumer vulnerability framework was used as the theoretical framework to examine how disadvantaged consumer characteristics and vulnerable consumer characteristics are associated with mistreatment and compromised accounts. Consumers in vulnerable states, due to low financial capability, cognitive decline, material hardships, financial shocks, and more exposure to various financial services, were more likely to report experiencing mistreatment and having their financial accounts compromised. Consumers from higher socio-economic status were more likely to have been victims of mistreatment and compromised accounts in financial services. These findings offer implications for consumer financial education and protection.

The Unpreventable Emotional Telecom Fraud —— "Pig-Butchering Scam"

It is well-established that the position of fraud crime has gradually shifted from traditional offline fraud to online telecom fraud. Among them, “Pig-Butchering Scam”, as a new type of fraud, was listed as one of the ten most prevalent fraud crimes by the National Anti-Fraud Center of China in February 2021. This study focuses on the victims of “Pig- Butchering Scam” cases, aiming to find out what common susceptibility traits or potential victimization factors the victims have, and how to cut off their false representations from the “susceptibility” to the behavioral dimension through effective interventions, in order to refine the psychological induction mechanism of emotion-based telecom fraud through this study. The purpose of this study is to refine the psychological induction mechanism of emotional telecommunication fraud. We have conducted field surveys and semi-structured interviews on victims’ personalities and analyzed their common characteristics. The results were similar to our hypothesis: the vast majority of victims generally showed a tendency to have low self-identity in the dimension of self-esteem, especially interpersonal-social self-esteem. This result suggests that people with low self-esteem, especially those with low interpersonal social self-esteem, are more likely to be potential victims of the “Pig-Butchering Scam”.

A Bagged Ensemble Convolutional Neural Networks Approach to Recognize Insurance Claim Frauds

Fighting fraudulent insurance claims is a vital task for insurance companies as it costs them billions of dollars each year. Fraudulent insurance claims happen in all areas of insurance, with auto insurance claims being the most widely reported and prominent type of fraud. Traditional methods for identifying fraudulent claims, such as statistical techniques for predictive modeling, can be both costly and inaccurate. In this research, we propose a new way to detect fraudulent insurance claims using a data-driven approach. We clean and augment the data using analysis-based techniques to deal with an imbalanced dataset. Three pre-trained Convolutional Neural Network (CNN) models, AlexNet, InceptionV3 and Resnet101, are selected and minimized by reducing the redundant blocks of layers. These CNN models are stacked in parallel with a proposed 1D CNN model using Bagged Ensemble Learning, where an SVM classifier is used to extract the results separately for the CNN models, which is later combined using the majority polling technique. The proposed method was tested on a public dataset and produced an accuracy of 98%, with a 2% Brier score loss. The numerical experiments demonstrate that the proposed approach achieves promising results for detecting fake accident claims.

Identification of Illicit Conservation Treatments in Fresh Fish by Micro-Raman Spectroscopy and Chemometric Methods.

In the field of food control for fresh products, the identification of foods subjected to illicit conservation treatments to extend their shelf life is fundamental. Fresh fish products are particularly subjected to this type of fraud due to their high commercial value and the fact that they often have to be transported over a long distance, keeping their organoleptic characteristics unaltered. Treatments of this type involve, e.g., the bleaching of the meat and/or the momentary abatement of the microbial load, while the degradation process continues. It is therefore important to find rapid methods that allow the identification of illicit treatments. The study presented here was performed on 24 sea bass samples divided into four groups: 12 controls (stored on ice in the fridge for 3 or 24 h), and 12 treated with a Cafodos-like solution for 3 or 24 h. Muscle and skin samples were then characterized using micro-Raman spectroscopy. The data were pre-processed by smoothing and taking the first derivative and then PLS-DA models were built to identify short- and long- term effects on the fish's muscle and skin. All the models provided the perfect classification of the samples both in fitting and cross-validation and an analysis of the bands responsible for the effects was also reported. To the best of the authors' knowledge, this is the first time Raman spectroscopy has been applied for the identification of a Cafodos-like illicit treatment, focusing on both fish muscle and skin evaluation. The procedure could pave the way for a future application directly on the market through the use of a portable device.

Reputation Systems: A framework for attacks and frauds classification

Reputation and recommending systems have been widely used in e-commerce, as well as online collaborative networks, P2P networks and many other contexts, in order to provide trust to the participants involved in the online interaction. Based on a reputation score, the e-commerce user feels a sense of security, leading the person to trust or not when buying or selling. However, these systems may give the user a false sense of security due to their gaps. This article discusses the limitations of the current reputation systems in terms of models to determine the reputation score of the users. We intend to contribute to the knowledge in this field by providing a systematic overview of the main types of attack and fraud found in those systems, proposing a novel framework of classification based on a matrix of attributes. We believe such a framework could help analyse new types of attacks and fraud. Our work was based on a systematic literature review methodology.

Distribution of Fraud Using Electronic Payment Means (Article 159.3 Criminal Code of the Russian Federation) from Related Crimes

The article is devoted to the study of the topical issue in the domestic theory of criminal law of delimiting fraud using electronic means of payment from related offenses. Based on the analysis of the circumstances of the legislative definition of Art. 159.3 of the Criminal Code of the Russian Federation, existing points of view in the science of criminal law and materials of law enforcement practice, criteria are distinguished for distinguishing the type of fraud under study from related offenses. The article substantiates that the objective side of fraud using electronic means of payment: implies the presence of deceit or breach of trust; characterized by the use of electronic means of payment; the use consists not in simply securing the transaction, but in the direction of the actions of the perpetrator to mislead the victim regarding the preparation, certification and transmission of the order in order to transfer funds within the framework of the applicable forms of cashless payments using information and communication technologies.

Identification of Fish Species and Targeted Genetic Modifications Based on DNA Analysis: State of the Art

Food adulteration is one of the most serious problems regarding food safety and quality worldwide. Besides misleading consumers, it poses a considerable health risk associated with the potential non-labeled allergen content. Fish and fish products are one of the most expensive and widely traded commodities, which predisposes them to being adulterated. Among all fraud types, replacing high-quality or rare fish with a less valuable species predominates. Because fish differ in their allergen content, specifically the main one, parvalbumin, their replacement can endanger consumers. This underlines the need for reliable, robust control systems for fish species identification. Various methods may be used for the aforementioned purpose. DNA-based methods are favored due to the characteristics of the target molecule, DNA, which is heat resistant, and the fact that through its sequencing, several other traits, including the recognition of genetic modifications, can be determined. Thus, they are considered to be powerful tools for identifying cases of food fraud. In this review, the major DNA-based methods applicable for fish meat and product authentication and their commercial applications are discussed, the possibilities of detecting genetic modifications in fish are evaluated, and future trends are highlighted, emphasizing the need for comprehensive and regularly updated online database resources.

Blockchain and machine learning for data analytics, privacy preserving, and security in fraud detection

Blockchain technology has emerged as a revolutionary distributed ledger system with the potential to transform various industries, including finance, supply chain, healthcare, and more. However, the decentralized nature of blockchain introduces unique challenges in terms of fraud detection and prevention. This abstract provides an overview of the current state of research and technologies related to fraud detection in blockchain technology-based systems. The paper begins by discussing the fundamental characteristics of blockchain, highlighting its immutability, transparency, and decentralization. These characteristics provide a promising foundation for ensuring data integrity and security but also pose significant challenges in detecting and mitigating fraudulent activities. Next, the paper explores various types of fraud that can occur in blockchain systems, such as double-spending, Sybil attacks, 51% attacks, smart contract vulnerabilities, and identity theft. Each type of fraud is explained along with its potential impact on the integrity and reliability of blockchain systems. To address these challenges, the paper presents an overview of existing fraud detection techniques in blockchain systems. These techniques encompass a range of approaches, including anomaly detection, machine learning algorithms, consensus mechanisms, cryptographic techniques, and forensic analysis. The strengths and limitations of each technique are discussed to provide a comprehensive understanding of their applicability in different scenarios. Furthermore, the paper highlights emerging trends in fraud detection research within the blockchain domain. These trends include the integration of artificial intelligence and blockchain technology, the use of decentralized and federated machine learning approaches, the development of privacy-preserving fraud detection mechanisms, and the utilization of data analytics and visualization techniques for improved detection and investigation. The paper concludes by emphasizing the importance of continuous research and development in fraud detection for blockchain technology-based systems. As blockchain adoption expands across industries, it is crucial to enhance the security and trustworthiness of these systems by effectively detecting and preventing fraud. Future directions for research and potential challenges are also discussed, encouraging further exploration in this vital area of study.