Online Identity Theft Research Articles

Online and Terrestrial Identity Theft: A Comparison of Victims and Examination of Reporting Decisions Across Modalities

The current study examines whether identity theft that occurs online differs from terrestrial identity theft, and the correlates of reporting across modalities. Findings from two samples (online n = 1,087; terrestrial n = 371) from the 2016, 2018, and 2021 waves of the National Crime Victimization Survey’s Identity Theft Supplement indicate that terrestrial identity theft led to greater levels of distress and financial losses than online identity theft, and was more often reported to police. Multivariate findings indicate that distress levels and knowledge of the person who committed the offense were positively associated with odds of reporting online identity theft, but not terrestrial identity theft. The article highlights the importance of acknowledging the modality of identity theft, and offers suggestions for policy.

Sự tin tưởng của khách hàng đối với dịch vụ ngân hàng điện tử trong bối cảnh đánh cắp danh tính trực tuyến: Nghiên cứu thực nghiệm trên địa bàn Hà Nội

The purpose of this study is empirical research to upgrade customer trust in e-banking platforms through practical e-banking service quality, customer satisfaction and the fear of online identity theft. Data was collected through structured questionnaires from 188 individual e-banking customers in Hanoi during the period from April to June 2023. To test hypotheses, the structural equation modeling (SEM) method was used. The findings revealed that e-service quality aspects have improved customer satisfaction and enhanced their trust, at the same time, customer trust improves as they feel their fear of identity theft diminishing. The results of this study provide useful information for commercial bank managers to consider aspects of e-banking service quality to achieve satisfaction, trust and a better understanding of the impact of fear of online identity theft on customer trust in the context of online identity theft increased in Vietnam.

Assessing E-commerce Adoption Determinants in Saudi Arabia: Impact of Financial Loss and Identity Theft

The study’s is to assess how Saudi Arabian visitor’ use of online shopping is affected by financial loss and identity theft. The association between financial loss, identity theft, and adoption of e-commerce in Saudi Arabia was investigated in this study using a quantitative research technique. Data were collected by structured questionnaires, and the findings were analysed utilising structural equation modelling (SEM) in Smart PLS. The analysis shows that visitors from Saudi Arabia tend to be more worried about money loss as well as online identity theft. This study is an innovative attempt to look at the e-commerce habits of Saudi visitors. By shedding light on the issues of identity theft and financial loss during online purchases in the digital age, it contributes to the small amount of knowledge currently scarce in this field.

COMPOSITE BEHAVIOURAL MODELLING FOR IDENTITY THEFT DETECTION IN ONLINE SOCIAL NETWORK

With this effort, we want to provide a pathway from raw behavioral data to a behavioral model that can identify online identity theft effectively, quickly, and robustly. We zero in on this problem in OSNs, where users often keep composite records of their behaviors, including offline check-ins and online user-generated content (UGC), which is multimodal and of poor quality. We verify that various record dimensions have a complementing impact when modeling users' behavioral patterns, which is an informative discovery. We recommend a combined (rather than fused) model to record aspects of a user's composite behavior that occur both online and offline in order to fully take use of this complimentary impact. We test the suggested combined model on two real-world datasets, Foursquare and Yelp, and compare it to both standard models and their combined model. Our model beats the current ones, according on the experimental data. The area under the receiver operating characteristic curve (AUC) values were 0.956 for Foursquare and 0.947 for Yelp, respectively. In example, with a disturbance rate (false-positive rate) of less than 1%, the recall (true positive rate) may reach as high as 72.2% in Yelp and 65.3% in Foursquare.

COMPOSITE BEHAVIORAL MODELING FOR IDENTITY THEFT DETECTION MIXTURE OF CLINICAL CONCEPTS

In this work, we aim at building a bridge from coarse behavioral data to an effective, quick-response, and robust behavioral model for online identity theft detection. We concentrate on this issue in online social networks (OSNs) where users usually have composite behavioral records, consisting of multidimensional low-quality data, e.g., offline check-ins and online user-generated content (UGC). As an insightful result, we validate that there is a complementary effect among different dimensions of records for modeling users’ behavioral patterns. To deeply exploit such a complementary effect, we propose a joint (instead of fused) model to capture both online and offline features of a user’s composite behavior. We evaluate the proposed joint model by comparing it with typical models and their fused model on two real-world datasets: Foursquare and Yelp. The experimental results show that our model outperforms the existing ones, with the area under the receiver operating characteristic curve (AUC) values 0.956 in Foursquare and 0.947 in Yelp, respectively. Particularly, the recall (true positive rate) can reach up to 65.3% in Foursquare and 72.2% in Yelp with the corresponding disturbance rate (false-positive rate) below 1%. It is worth mentioning that these performances can be achieved by examining only one composite behavior, which guarantees the low response latency of our method. This study would give the cybersecurity community new insights into whether and how real-time online identity authentication can be improved via modeling users’ composite behavioral patterns.

Evaluating E-Commerce Engagement Factors In Saudi Arabia: Financial Loss, Identity Theft And Privacy Policies

Purpose: The purpose of this study is to investigate the influence of financial loss, identity theft, and privacy protection policies on the willingness of tourists in Saudi Arabia to engage in e-commerce. Theoretical framework: This study examines Saudi Arabian visitors' use of e-commerce, highlighting the consequences of financial loss, identity theft, and privacy laws. The study employs Smart PLS and structured questionnaires, underpinned by a theoretical framework of trust and security, to uncover heightened fears over online identity theft. Policies protecting privacy become essential, boosting customer confidence and promoting e-commerce. The study adds to the scant amount of information in this field by emphasising the role that regulations play in maintaining transaction security and promoting user confidence. Design/Methodology/Approach: This study used a quantitative research methodology to examine the relationship between financial loss, identity theft, privacy protection policies, and the willingness to engage in e-commerce in Saudi Arabia. Structured questionnaires were used to gather data, and Smart PLS was used to analyse the results using Structural Equation Modelling (SEM). Findings: The study reveals that Saudi Arabian tourists express more concern about online identity theft than financial loss. Privacy protection policies play a pivotal role in enhancing their trust and participation in e-commerce, underscoring the importance of regulatory measures for ensuring user confidence and online transaction security. Research, Practical & Social implications: This study highlights the unique worries that Saudi Arabian internet customers have, prioritising identity theft over money loss. Policies protecting privacy become an important middleman that is essential to fostering trust and promoting e-commerce. The findings encourage more investigation into the fundamental elements influencing user choices in study. Practically speaking, companies may improve tactics by giving strong privacy safeguards top priority. In order to promote a safe and reliable e-commerce environment that benefits customers and the expansion of Saudi Arabia's online market, it is socially vital to advocate for explicit privacy legislation. Originality/value: This study is a pioneering attempt to investigate Saudi Arabian tourists' e-commerce behaviour. It adds to the scarce body of knowledge in this area by illuminating the importance of privacy protection policies in fostering consumer trust.

Do IT users behave responsibly in terms of cybercrime protection?

This study aims to analyze the behaviour of IT users regarding their personal protection against potential cybercrimes. The research data set is based on surveys conducted by the European Commission in 2020-2021 for 35 European countries. Canonical analysis revealed that 66.67% of cybercrime cases (Phishing, Pharming, Online identity theft, etc.) determine individuals' choice of personal protection method (using a security token, social media logins, electronic identification, etc.). Kohonen's self-organizing maps were used to form 9 clusters of countries depending on the attitude of IT users to personal cybersecurity. The map results showed that individuals behave less responsibly using a security token, electronic identification certificate or card, pin code list or random characters of a password, and other electronic identification procedures. Users from Denmark, the Netherlands, Iceland, Norway, the UK, Austria, and Finland were the most responsible Europeans in terms of personal protection, while people from Bulgaria, Romania, Serbia, Albania, North Macedonia, Bosnia and Herzegovina were the least conscientious about protection.

Cyber Crime and Its Fear in Women

Cybercrime is a growing problem globally, with women being more vulnerable to its effects than men. Women are particularly susceptible to online harassment, stalking, revenge porn, and identity theft. Despite the prevalence of cybercrime and its adverse effects on women, little is known about how women perceive and respond to these types of crimes. This research study aims to explore the fear of cybercrime among women and the impact it has on their online behavior and daily routines. The paper reviews existing literature on cybercrime and gender, survey data related to attitudes towards cybercrime, and interviews with women on their experiences with cybercrime.

Effects of Individual and Contextual Dimensions on an Aggregate Measure of Cybervictimization

ABSTRACT Cybervictimization is a significant challenge and increasing concern. This study explored the predictors of an aggregate measure of six different types of cybervictimization, incorporating property (online consumer fraud, online identity theft), interpersonal (cyberbullying and cyberstalking), as well as phishing and malware infection crimes. An online survey was self-administered to 726 individuals, measuring sociodemographic variables and routine activity variables, stemming from Routine Activities Theory (RAT). Of the 726 individuals, 440 were already victims of at least one cybercrime. Communicating or giving personal information to unknown individuals doubled the likelihood of being victimized online. Education increased the likelihood of victimization, while higher income was associated with a lower likelihood of online victimization. These results are discussed in relation to the RAT framework and existing empirical studies that have applied it to explain online victimization.

Individual residence and identity theft: how residential characteristics shape exposure and risk of offline and online identity theft victimization

Purpose The purpose of this study is to examine the effect of micro-level place on identity theft victimization. This study uses the 2016 Identity Theft Supplement (ITS) to investigate whether aspects of an individual’s residence affect their likelihood of becoming identity theft victims. Design/methodology/approach The authors conduct logistic regressions of whether a respondent was an identity theft victim in the past year using the following variables as key predictors: number of housing units in a residence, whether the respondent operates a business out of their residence and if residence access is restricted. Findings The results suggest that location influences the likelihood of identity theft to a modest degree though some aspects of location (possibly those related to rewards perceptions) may be more relevant than others. Meanwhile, though location may influence initial target selection, whether someone is victimized may be more dependent on factors such as personal behavior. Originality/value To the best of the authors’ knowledge, this manuscript represents one of the first investigations into the relationship between microlevel place and the incidence of identity theft. Furthermore, it provides evidence that one does exist which bears further inquiry.

The impact of online identity theft on customers’ usage intention of e-banking transactions in uncertain context

During the fierce national and international competition, many organizations are taking digital technology into action to provide new products to customers via modern interactive channels (Sepashvili, 2020). This research is conducted to provide empirical evidence on the effects of online identity theft on consumers’ usage intention to engage in e-banking transactions in uncertain context. Using structural equation modeling (SEM) and survey data from 441 individuals, the main findings of the study are: 1) Security and privacy concerns (SAPC) should be divided into two sub-factors: a) e banking security and privacy concerns, and b) internet security and privacy concerns. It differs from previous studies that combined the Internet and e-banking. We found that trust (T) is negatively impacted by Internet concerns and positively impacted by e-banking concerns; 2) Trust positively impacts the usage intention of e banking (UIEB); 3) Fear of online identity theft (FOIT) has a positive effect on trust; 4) FOIT positively impacts SAPC. Theoretically, this study has focused on investigating potential determinants influencing customer intention when gradually adapting to new technology services. In practice, the proposed study will go into depth on the limitations faced by clients in the hidden dimension, which prevent them from engaging in online banking activities.

Oversharing on Social Media: Anxiety, Attention-Seeking, and Social Media Addiction Predict the Breadth and Depth of Sharing.

Oversharing on social media by adolescents is a considerable problem in the digital age, and has the potential to instigate online shaming, cyberbullying, identity theft, and other security risks. To date, oversharing has not been comprehensively studied and there is scarce understanding of the possible psychological conditions that may underlie this maladaptive online behavior. This study aimed to measure online oversharing and its potential psychological correlates among adolescents. Data were collected from 352 Iranian adolescent social media users (270 girls and 82 boys; Mage = 16.38, SD = 1.71). The Online Oversharing Inventory, developed for this study, demonstrated unidimensionality and excellent internal consistency. Further results showed that boys overshared significantly more on social media than girls did. Anxiety, attention-seeking, and social media addiction were significantly associated with elevated levels of online oversharing. Results show that the Online Oversharing Inventory is a brief and robust tool for the assessment of high frequency self-disclosure on social media. The findings suggest that anxiety, attention-seeking, and problematic use of social media may predispose adolescents to overshare personal information online.

Exploring the determinants of victimization and fear of online identity theft: an empirical study

The present study aims at understanding what factors contribute to the explanation of online identity theft (OIT) victimization and fear, using the Routine Activity Theory (RAT). Additionally, it tries to uncover the influence of factors such as sociodemographic variables, offline fear of crime, and computer perception skills. Data for the present study were collected from a self-reported online survey administered to a sample of university students and staff (N = 832, 66% female). Concerning the OIT victimization, binary logistic regression analysis showed that those who do not used credit card had lower odds of becoming an OIT victim, and those who reported visiting risky contents presented higher odds of becoming an OIT victim. Moreover, males were less likely than females of being an OIT victim. In turn, fear of OIT was explained by socioeconomic status (negatively associated), education (positively associated) and by fear of crime in general (positively associated). In addition, subjects who reported more online interaction with strangers were less fearful, and those reported more avoiding behaviors reported higher levels of fear of OIT. Finally, subjects with higher computer skills are less fearful. These results will be discussed in the line of routine activities approach and implications for online preventive behaviors will be outlined.

Composite Behavioral Modeling for Identity Theft Detection in Online Social Networks

In this work, we aim at building a bridge from coarse behavioral data to an effective, quick-response, and robust behavioral model for online identity theft detection. We concentrate on this issue in online social networks (OSNs) where users usually have composite behavioral records, consisting of multidimensional low-quality data, e.g., offline check-ins and online user-generated content (UGC). As an insightful result, we validate that there is a complementary effect among different dimensions of records for modeling users’ behavioral patterns. To deeply exploit such a complementary effect, we propose a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">joint</i> (instead of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">fused</i> ) model to capture both online and offline features of a user’s composite behavior. We evaluate the proposed joint model by comparing it with typical models and their fused model on two real-world datasets: Foursquare and Yelp. The experimental results show that our model outperforms the existing ones, with the area under the receiver operating characteristic curve (AUC) values 0.956 in Foursquare and 0.947 in Yelp, respectively. Particularly, the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">recall</i> (true positive rate) can reach up to 65.3% in Foursquare and 72.2% in Yelp with the corresponding <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">disturbance rate</i> (false-positive rate) below 1%. It is worth mentioning that these performances can be achieved by examining only one composite behavior, which guarantees the low response latency of our method. This study would give the cybersecurity community new insights into whether and how real-time online identity authentication can be improved via modeling users’ composite behavioral patterns.

Identity Theft Detection Using Machine Learning

Abstract: Online Identity Theft is known to be quite possibly the most genuine and developing dangers to people and organizations for the past decade because of the colossal financial harm caused by it. It is a critical form of cybercrime which uses information such a victim’s name, bank details, email address, passwords, passport or identification details, and other valuable information to gain access to accounts. This aim of this research is to make use of Machine Learning algorithms for the detection of such crimes. Keywords: identity theft; cybercrime; Machine Learning; detection; algorithms

Rethinking the Knowledge Economy of e-Dating in Romance Stories: Hypertexting G. Homans’ Social Exchange Theory

Millions of single adults use dating websites like eHarmony, Anastasiadate.com, Match.com, Chemistry.com and technologies like the mobile dating app Tinder to seek out online partners. Some daters succeed, but most of them fail in the end and become dissatisfied. The online technology presents with many advantages such as easy access to multitudes of potential dates; however, the problematic is that, as a metanarrative of dating power, ICTs do not function in a virtual vacuum but are constructed by the social experience of people in love and sexuality, for example, in African indigenous and modern societies ǎ la longue durée. The online dating industry often disembeds this social experience from its services and this constitutes, paradoxically, its major flaw. Consequently, the industry is designed narrowly to rationalize romanticism as a scientific algorithm that follows particular rules and regulations instead of proposing the complex character of knowledge about dating to prospective daters and this constitutes a serious menace to its long term sustainability. These technodigital flaws have to do with the paradox of virtual rationalism, lack of commitment in online daters, who do not meet offline; shallowness and fatigue in the mindset of online singles, scamming, lies telling, identity theft and stalking, mismatching from algorithms between singles and so on. Drawing critical insights from the structuralist positionality of George Homans’ social exchange theory and from critiques of romance stories, the paper suggests that, in this age of the knowledge economy, e-dating should become a productive service that minimizes the artificiality of economic rationalism embedded in digital contacts, profile browsing, algorithmic matching, the reading of love by apps and tread lightly on all forms of economic determinism. e-Dating should prioritize tacit knowledge from critical literature narratives that can enable us to suggest new humanistic functionalities for skype, ch

Correlation Impact by Random Forest Towards Prediction of Phishing Website

Phishing is an online identity theft that lure unsuspecting victims into phishing website that asks for their personal information such as financial credentials or online access. The most obvious phishing attacks use spam emails to lure victims into visiting its phishing website. The less obvious attack is when a phisher spoofes legitimate sites to bring the victims to the phishing website by presenting a visually similar websites. To address this issue, this paper focuses on the effectiveness of the Random Forest algorithm in predicting a website whether a phishing or lieitimate website. The prediction model is developed using the classfication methodology and the results revealed that the prediction accuracy of Random Forest in only 66.66%. This is due to potential high correlation among the features when training the dataset since each Random Tree in the forest should protect each other from individual errors. In the future, this project is hoped to investigate features selection of the same dataset because the phishing website prediction model requires features that at least some predictive power.

The impact of online identity theft on customers’ willingness to engage in e-banking transaction in Ghana: A technology threat avoidance theory

Until recently, studies regarding e-banking transactions have focused more on motivational factors that trigger the intention to accept and use the e-banking transaction, rather than the de-motivat...

Target Suitability as a Determinant of Online Identity Theft: Case of University Students in Khyber Pakhtunkhwa Province of Pakistan

This research study aimed to measure the relationship of online target suitability with the chances of online identity theft (OIT) that faced by the universities students of Khyber Pakhtunkhwa (KP). The concept of target suitability was adopted from Routine Activity Theory (RAT). A descriptive survey research approach was adopted in this study. Universities going students of KP formed the population of this study. 800 students were selected from the 6 universities of KP. The data was analyzed using multiple regression techniques. The results reveal that the target suitability in online activities of the young adults increases the likelihood of OIT.

Fear of Online Consumer Identity Theft: Cross-Country Application and Short Scale Development

The growing internationalization of electronic commerce demands the establishment of the cross-national validity of theoretical concepts. An important concept in e-commerce is consumers’ fear of online identity theft (FOIT), which impedes consumers’ willingness to engage in online transactions and can negatively affect e-commerce revenues. The present study validates the consumer FOIT scale developed in Germany by Hille et al. (2015) in a cross-cultural setting and proposes an abbreviated version of the scale, which is approximately 35% shorter than the original. Established validation procedures with samples of online consumers from Germany, the United States, and Japan demonstrate the reliability, validity, and cross-national applicability of the short FOIT scale. In particular, this study extends Hille et al. (2015) research by examining and revealing the impact of FOIT on consumers’ prevention-focused responses. This research offers implications for both research and e-commerce managers.