Online Fraud Research Articles

Кибертерроризм – как важнейшая угроза национальной безопасности

With the incredible and powerful development of telecommunications net-works that we are witnessing in the third decade of the 21st century, international cyber-terrorism is also becoming more widespread. As a result of this phenome-non, individuals or entire international terrorist groups and organizations seek, thanks to the anonymity provided to them by cyberspace, to carry out various types of threats without any threat of identifying these criminals, their possible capture, or even physical elimination, as this happens in cases of elimination of real, not virtual, terrorist attacks. Today, international terrorist groups are increasingly using such tools to carry out attacks as DoS and DDoS attacks - denial of service, as well as other criminal methods, including phishing, online fraud, etc. Currently, international cyberterrorism poses a serious threat not only to the economy of the entire world community, but is also dangerous for various critical infrastructure facilities. In this regard, cyberterrorism has the highest level of threat to national security compared to other possible attacks by international terrorists. In this regard, the author proposes a set of measures that must be taken to prevent attacks by international cyberterrorists.

Voice analysis system for detection of vishing using deep learning

For many years, telecom fraud has caused significant financial harm to Indian telecommunications users. Traditional approaches for identifying telecom fraud frequently center on boycotting of faux phone numbers. Attackers, on the other hand, could merely escape discernment by modifying their phone numbers, which is fairly straightforward with VoIP (Voice over IP).To address this issue, this method detects telecommunication fraud supporting the substance of a spoken language rather than merely the caller's sign. This paper collects chronicles of telecommunication deceit, above all, from press sources and social platforms. To make datasets, our planned model utilizes machine learning techniques to look at knowledge and opt for high-quality descriptions from antecedently gathered knowledge. After that, Natural language processing is employed to draw out characteristics from the text- based data. Then, for extra telecommunication fraud detection, criteria to acknowledge identical material within the same call are formed. To spot telecommunication fraud online, the system provides an associate degree android application that will be loaded on a customer's smartphone. Once an associate degree incoming fraud decision is answered, the program will dynamically measure the call's contents to sight fraud. Our findings demonstrate that the system will effectively safeguard clients.

How Safe You Are on Social Networks?

Millions of individuals use Twitter, one of the most prominent social media sites, to exchange information, broadcast tweets, and follow other users. Twitter being an open application programming interface is vulnerable to attacks from fake accounts. Fake accounts are primarily used for advertising and marketing, defamation of an individual, consumer data acquisition, increasing fake blog or website traffic, sharing wrong information, online fraud, and control. Fake accounts are disruptive to both users and service providers, thus it's critical to recognize and filter out such information on social media. This paper presents a technique for detecting fake Twitter accounts using the feature set mapped to Twitter’s rules and policies to flag suspicious accounts. To choose the apt subset of features from the original feature space, feature selection techniques such as information gain and correlation were used. Users have been classified using a Logistic Regression classifier with the detection accuracy of 93.5 percent after being trained on the data of about 1,00,000 Twitter users. Furthermore, an algorithm for classifying suspicious users as Fake profiles has been presented. The results of the experiments show that the suggested model outperforms competitive state-of-the-art research in the majority of circumstances.

Level of Cybercrime Threat During the Outbreak of COVID-19 Pandemic: A Study in Malaysia

Cybercrime threat has shown a sudden increase during the enforced stay-at-home order due to the outbreak of the COVID-19 pandemic. Thus, empirical research was conducted in providing substantial evidence regarding the level of cybercrime threats in Malaysia during the outbreak of the COVID-19 pandemic. A quantitative approach was used to collect data among 332 respondents across Malaysia. The finding stipulated that a large number of respondents have experienced a high level of online phishing/malware distribution (72.9%), a moderate level of online fraud (69.2%), and a moderate level of online sexual harassment (87.7%). The move to explore the level of cybercrime threat experienced by the public during the outbreak of the COVID-19 pandemic is essential to detect, disrupt, and mitigate cybercrime threats during unprecedented situations.

The Drivers of a Digital Signature System Adoption: Evidence from Finance and Information System Departments

Background: With the massive e-commerce transactions and document transfers, reliable system protection is needed. A digital signature is a tool that consists of encryption and decryption algorithms in a secret key to prevent data theft and online fraud. Objective: This research proposes an integrated technology-organization-environment (TOE) and the unified theory of acceptance and use of technology (UTAUT) to determine the factors affecting consumer intention to adopt the digital signature system. This research uses finance and information system departments’ perspectives in various industries. Methods: The analytical method is the Structural Equation Modeling (SEM) approach using the Smart Partial Least Square statistical version 3.0 software to examine the hypothesized connections between latent variables. Results: The results show that support from top management, size of the enterprise, and social influence have significant and positive effects on digital signature adoption. Meanwhile, user involvement and perceived simplicity have a negative effect on the adoption of a digital signature system in finance and information system departments. Conclusion: The current research suggests that executive levels in the finance and information system departments encourage the adoption of digital signature tools in doing daily tasks to increase efficiency. Keywords: Digital signature, consumer intention, finance and information system, structural equation modeling, TOE and UTAUT

Empirical Analysis of Machine Learning Algorithms on Detection of Fraudulent Electronic Fund Transfer Transactions

Online financial systems like electronic funds transfers (EFT) are heavily dependent on the public Internet. A diverse set of Internet traffic is generated from the use of different online financial platforms. The analysis of raw Internet traffic fails to identify any anomalous behavior in financial transactions. A similar result is obtained when we apply application layer anomaly detection in financial transactions. In this article, we propose a machine learning-based multi-layer framework which will detect and classify anomalous financial transactions. The proposed framework can help a financial service provider to avoid incidents like intrusions and online frauds. It also provides a secure mechanism to detect network anomalies in financial transactions to augment the credibility of such online financial platforms or gateways.

Why do fraud victims get blamed? Lerner’s Belief in a Just World and its application to victims of online fraud

PurposeVictims of online fraud face a high level of blame from their families, friends, professionals, the broader community and often from themselves. Victims are commonly perceived as stupid, gullible and undeserving of justice. The reasons for this are under-researched, and there are currently no satisfactory explanations of why victim-blaming occurs so frequently in cases of online fraud. This paper aims to propose a potential theoretical explanation for the high level of blame experienced by online fraud victims.Design/methodology/approachLerner’s Belief in a Just World (BJW) theory is posited as a helpful theoretical explanation for the high level of blame directed towards victims of online fraud.FindingsThis paper argues that Lerner’s BJW theory is a helpful framework for understanding the blame faced by victims of online fraud because it posits that behavioural responsibility (a trait commonly ascribed to online fraud victims) is central to perceived blameworthiness; and that compensation for a crime determines the level of blame directed towards victims. As victims of online fraud are exceptionally unlikely to receive any type of compensation (whether monetary or otherwise), BJW may help explain the blame directed towards victims.Originality/valuePrior scholarship predominantly understands the blame faced by online fraud victims through the lens of Nils Christie’s (1986) “ideal victim” thesis. This paper presents an advance over this existing understanding by illustrating how BJW provides a more detailed explanation for victim blame in online fraud.

Experience of prevention e-commercial fraud in the USA

The article analyzes the prevention of electronic trade and commercial fraud in the United States of America. It is noted that the scientific area of research of modern fraud requires constant empirical updating and theoretical understanding in the field of Crivinology and Victimology, in particular, in the area of fraud research in the sphere of electronic commerce and trade.
 The basis of the scientific Crimean-logical analysis was a complex combination of philosophical (in particular, dialectic), general scientific (synthesis, analysis, indouction, and generalization) and special-scientific methods.
 For the purpose of this work, in particular, the peculiarities of prevention of electronic trade and commercial fraud in the USA are justified, namely: 1) the rules of special laws on prevention of online fraud in the sphere of electronic commerce and trade are described; 2) the subjects which carry out work on prevention of this type of criminal offense are defined; and 3) considered the latest technologies used in this field. Special attention is paid to the formal-established rules of protection of online shops of the USA from various kinds of threats of fraud, which are aimed at reducing their risk in the sphere of electronic trade and considered important tools of detection and prevention of fraud.
 The conclusions set out universal mechanisms for effective prevention of criminal offenses in this sphere, the elaboration of which will further develop conceptual measures of state policy on counteraction to fraud; and create a program of action for law enforcement bodies.

Challenges in Adoption of Digital Health Education among Educated Youth in Pakistan

This study attempts to examine the challenges in the adoption of digital health technology among educated youth in Pakistan. Using qualitative research methods, opinions of male and female students of public and private sector universities in Islamabad were gathered through eight Focus Group Discussions (FGDs). The study themes included: Complexity of language and medical terminology on the internet, lack of Information and Communication Technology (ICT) skills, less reliability of different websites, and threat to privacy. The study found that several factors such as poor facilitations conditions, institutional negligence, problematic medical jargon, online frauds, and privacy insensitivity are hampering the access to eHealth services among students of universities in Islamabad. As the global health systems are moving towards eHealth services, the lack of technological knowledge of the patients may harm their access to health services. Thus, there is a need to minimize the barriers to digital health education at the institutional level.

SUSTAINABILITY RISK MANAGEMENT AND INFORMATION TECHNOLOGY GOVERNANCE IN MALAYSIA

Sustainability encompasses more than green and environmental protection. That is why the United Nations' sustainable development goals (SDGs) comprise 17 targets aimed at achieving global sustainability through shared prosperity and peace for people and the planet, both at present and in the future. SDG-9, which focuses on resilient infrastructure, sustainable industrialisation, and innovation, calls for investment in information technology (IT) to support sustainable development and community empowerment. Regardless of the amount to which IT can assist in accomplishing goals, it requires adequate control. Otherwise, it will exacerbate threats to the environment and society, as well as to the corporate organisation. IT governance is primarily motivated by the need for an organisation's risks to be transparent and its stakeholder values to be protected. By contrast, sustainable risk management (SRM) is a systematic strategy to managing an organisation's environmental, social, and governance risks (ESG). This conceptual paper discusses the function of information technology governance and its effect on the practise of SRM in Malaysia. The study highlights four IT governance functions that have an impact on sustainability risks: protection against reputational risk, guaranteeing equal access, reducing environmental impact, mitigation of online fraud and improper business, and protecting data integrity and confidentiality. This study would shed light on the sustainability hazards associated with information technology and raise awareness of their influence on society and the environment. As a result, it is envisaged that the objectives for IT investment are met while also mitigating IT risks. Hopefully, this study can serve as a stimulus for further research on related topics of IT governance and sustainable risk management on a worldwide scale, and particularly in the Malaysian context.

Convergence of Traditional and Online Property Crime Victimization in a City with Little Offline Crime

ABSTRACT This paper analyzes the correlates of traditional (burglary, vehicle theft, theft from vehicles, and pickpocketing) and online property crime (data theft and online fraud), with particular attention given to the relation between them and the risk of multiple victimizations. Data are gathered from a large and representative victimization survey conducted in a Swiss city (N = 7,885). The findings suggest that both traditional and online property victimization are related positively to the participants’ lifestyle routines, physical and online protection measures, and educational level. Men, young persons, those employed actively, and university graduates are overrepresented among the multiple victims of online-offline property victimization.

Reduction of Online Fraudulent Activities in Freelancing Sites Using Blockchain and Biometric

Digital freelancing refers to hiring potential employees to work on specific projects on a contract basis by organizations, companies, and individuals. Existing freelancing systems are based on client-server models and managed in a centralized way. Centralized freelancing systems are originating several issues: lack of trust, payment delays, central control over all operations, less reliability, online frauds, and lack of fairness. Hence, we propose a decentralized freelancing system based on blockchain and biometrics. Blockchain in the freelancing system makes contracts decentralized, and no one can control the interaction and deals between buyers and sellers. Biometric signatures on smart contracts in the freelancing system enhance the authenticity and validity of agreements between buyers and sellers. Our decentralized freelancing system is an online web-based platform based on blockchain and biometrics and built on Python. It makes the interaction and deals between buyers and sellers via the innovative approach of smart contracts. The proposed work illustrates the development, implementation, and functionalities of the freelancing system, such as registration as buyer or seller, logging in to the system, posting a job, bidding on jobs, hiring process, finalizing deals with smart contracts having a biometric signature of both parties and distributing smart contracts among all stakeholders via blockchain. Our system proves the fairness, clarity, security, and reliability in all processes of posting and hiring without the involvement of any central management authority.

On Social Experience, Prevention Consciousness and Network Fraud of College Students in Finance and Economics Based on Survey Data

With the development of the Internet, college students suffer from network fraud in many layers, which has aroused widespread concern in the society. Based on the questionnaire survey data of the current situation of college students suffering from online fraud in financial and economic colleges, this paper uses structural equation model to analyze the relationship between social experience, prevention awareness and college students suffering from online fraud. The study found that: (1) social experience not only has a significant direct effect on college students suffering from online fraud, but also has an indirect impact on college students suffering from online fraud through the pursuit of economic independence. (2) Prevention awareness has no significant direct effect on college students suffering from online fraud. Personal information protection plays a complete intermediary role between prevention awareness and college students suffering from online fraud. Based on the research results, it is proposed to strengthen the ideological and political education of college students, improve the awareness of risk prevention, build a long-term mechanism and link the comprehensive management of departments to prevent college students from suffering from online fraud and promote the healthy growth of college students.

“Credit Card Fraud” Detection Using Data Analytics A Comparative Analysis

Fraud events take place frequently which results in a huge financial loss. Fraud detections are dynamic and are not easy to identity. Data mining plays a vital role in detection of “Credit card fraud” done in fraudulent online transactions. Fraudsters use latest advanced methods which is an advantage. This process becomes challenging based on two major reasons -firstly, the profiles of users keep changing constantly and secondly, the datasets required for this are highly confusing. The overall performance of “Credit card fraud” detections is improved by sampling approach on the dataset. This research looks at fraud incidents in the context of real-life fraud transactions. A variety of machine learning methods and modelling approaches are used to combat each fraud. The goal of this study is to see how well logistic regression and K-nearest neighbour (KNN) perform on highly skewed “Credit card fraud” data. In order to assess the algorithm's robustness even further, noise is injected into the data sets. The major purpose of this study is to compare and contrast numerous methods for identifying fraud.

Sosialisasi Pentingnya Keamanan Digital di Era Revolusi Industri 4.0 di Desa Gajah Mati Bengkulu Tengah

This community service activity in the form of socializing the importance of digital security in the era of the industrial revolution 4.0 aims to help the residents of Gajah Mati village, Central Bengkulu, in getting information about technological advances and how to maintain digital security. The subjects in this service activity were the Head of Gajah Mati Village and his apparatus and all residents of Gajah Mati Village, Central Bengkulu. This socialization process is carried out by providing information about security and prevention in the face of technological advances and fraudulent fraud in cyberspace. The result of this community service activity is that it can help villagers know about technological advances, how to deal with various kinds of online fraud so that they can slightly reduce victims of cybercrime. The conclusion of this community service activity in Gajah Mati Village, Central Bengkulu, is that it can provide information about technological advances, use technology, one of which is the use of Android smartphones, and help the community in dealing with fraud - fraud in cyberspace so that citizens can think smart if face the problem of fraud - fraud in cyberspace because they have received information and how to overcome it through this socialization. So the victims of crimes in cyberspace are slightly reduced.

Usability and Security Testing of Online Links: A Framework for Click-Through Rate Prediction Using Deep Learning

The user, usage, and usability (3U’s) are three principal constituents for cyber security. The effective analysis of the 3U data using artificial intelligence (AI) techniques allows to deduce valuable observations, which allow domain experts to design practical strategies to alleviate cyberattacks and ensure decision support. Many internet applications, such as internet advertising and recommendation systems, rely on click-through rate (CTR) prediction to anticipate the possibility that a user would click on an ad or product, which is key for understanding human online behaviour. However, online systems are prone to click on fraud attacks. We propose a Human-Centric Cyber Security (HCCS) model that additionally includes AI techniques targeted at the key elements of user, usage, and usability. As a case study, we analyse a CTR prediction task, using deep learning methods (factorization machines) to predict online fraud through clickbait. The results of experiments on a real-world benchmark Avazu dataset show that the proposed approach outpaces (AUC is 0.8062) other CTR forecasting approaches, demonstrating the viability of the proposed framework.

Mahalanobis distance based accuracy prediction models for Sentinel-2 Image Scene Classification

ABSTRACT Over the years, due to the enrichment of paired-label datasets, supervised machine learning has become a prime component of any problem-solving. Examples include building classifiers for applications such as image/speech recognition, traffic prediction, product recommendation, virtual personal assistant (VPA), online fraud detection and many more. The performance of these developed classifiers is highly dependent upon the training dataset, and subsequently, without human intervention or true labels, the evaluation over unseen observations remains unknown. Using a statistical distance researchers did try to assess the model’s goodness-of-fit and compared multiple independent models. Nonetheless, given a train-test split and different classifiers built over the training set, the question ‘is it possible to find a prediction error using the relation between training and test set?’ remains unsolved. In this article, we propose a generalized statistical distance-based method measuring the prediction uncertainty at a new query point. To be specific, we propose a Mahalanobis distance-based Evidence Function Model to measure the misclassification caused by K-Nearest Neighbours (KNN), Extra Trees (ET), and Convolutional Neural Network (CNN) models when classifying Sentinel-2 image into six scene classes (Water, Shadow, Cirrus, Cloud, Snow, Other). The performance of the proposed method was assessed over two different datasets: (i) the test set, with an overall mean prediction uncertainty detection of 62.99%, 29.80% and 31.51%, leading to a mean micro-F1 performance of 67.89%, 39.30%, and 38.29% for KNN, ET, and CNN, respectively; (ii) a water-body set, with prediction uncertainty detection of 22.27%, 42.08%, and 27.67%, leading to a micro-F1 performance of 34.70%, 58.96%, and 43.32%, respectively.

Victimisation and the Fear of Cybercrime during the COVID-19 Pandemic: Experience of Undergraduate Students in Kenya

The victimisation model in the context of cyberspace suggests that previous cybercrime victimisation results in fear of cybercrime. Previous researchers have found mixed results in their findings. The current study uses five prevalent cybercrimes in Kenya, namely, impersonation, cyberbullying, online fraud, phishing, and computer virus, to establish the nature of the relationship between victimisation and the fear of cybercrime. A convenient sample of 55 university students pursuing a Bachelor’s degree in criminology at Dedan Kimathi University of Technology was used. Findings indicated that those who have experienced cyberbullying and impersonation and those who spend much time on social media are more fearful of cyberbullying. Moreover, those who have experienced online fraud and those who are less frequent shoppers are more fearful of online fraud, while those who have experienced phishing and those who receive a high number of spam emails are more fearful of hacking when opening links embedded in emails. Finally, those who have experienced computer viruses, as well as those who complete zero downloads per day, are more fearful of computer viruses. High internet usage, experiences of online fraud and phishing attacks and attempts which are positively related to fear of cyberbullying, can be attributed to COVID-19 times when most Kenyans were vulnerable and not working.

Phishing short URL detection based on link jumping on social networks

Nowadays, a large number of people frequently use social networks. Social networks have become important platforms for people to publish and obtain information. However, social networks have also become the main venue for hackers to initiate online fraud. Phishing is a common way used by hackers to launch online fraud on social networks. This paper proposes a method for detecting phishing short URL based on the link jumping. The method uses a hierarchical hidden Markov model with two-layer structure to describe the link jumping process after user clicking on short URL, so as to identify phishing short URL on social networks. The proposed method includes a training phase and an identification phase. In the identification phase, the average log-likelihood probability of the observation sequence is calculated. An experiment based on real datasets of Weibo is conducted to evaluate this method. The experiment results validate the effectiveness of this method.

The Integration of Legal Education and Mental Health Education of College Students in the Contemporary Network Environment Facing the Cultivation of Civic Awareness.

Since the world entered the era of network information, the influence of the Internet has been expanding day by day, and today's college students are deeply affected by the network environment, which has also brought unprecedented challenges to the moral education work of colleges and universities. The rule of law education for college students is a key point for the comprehensive implementation of the strategy of governing the country by law. How to enhance the effectiveness and recognition of the rule of law education for college students has become an important task of higher education. Therefore, strengthening the legal education of college students is not only an inevitable choice to fully implement the rule of law but also a realistic requirement to improve the level of higher education and realize the all-round development of college students. College students' mental health education is an important part of the talent training system of colleges and universities, and in-depth exploration of the ideological and political laws of college students' mental health education courses is an inevitable requirement for implementing the fundamental task of Lide Shuren. College students' mental health education courses must be integrated into the ideological and political concepts of the curriculum, reflect the political orientation of ideological and political work, embody the law of educating people with morality as the first, and embody the practical purpose of psychology to pay attention to personality improvement. It is necessary to optimize the content of education and teaching, excavate the elements of ideological politics in the curriculum, enrich the resources of ideological politics in the curriculum, and explore a new way of reforming the ideological and political education curriculum for college students from the aspects of deeply planting family and national feelings, enhancing political identity, strengthening cultural self-confidence, cultivating Chinese temperament, clarifying the meaning of life, strengthening mission responsibility, enhancing civic awareness, and developing law-abiding habits. Strictly regulate the behavior of contemporary college students in the online environment, give full play to the role of legal education, and reduce the incidence of online incidents such as online fraud and cyber violence. This paper puts forward some problems in the current legal education of college students in China and points out the root causes of these problems. Methods for structural reform and advanced cultural construction based on social development are proposed. From a strategic point of view, it is believed that only by managing the reform of legal education and cultivating civic awareness can we completely solve various contradictions and problems among college students in the network environment and pave the way for the development of college students.