Identity theft

About: Identity theft is a research topic. Over the lifetime, 2284 publications have been published within this topic receiving 31700 citations.

Technology of deception

Abstract: So Beijing's Olympic fireworks weren't real. But, as E&T reveals, deception is all around us, entertaining us, tricking our enemies and even making the sun shine. The paper presents the technology of deceptions that today's world, we are immersed in a sea of deception, not least within the virtual world we increasingly inhabit. The technology of the Internet has permitted the relatively benign deception inherent in social networking constructs such as Facebook and MySpace, and in online gameworlds such as RuneScape and Second Life. Sadly, it has also provided a new avenue for fraudulent deception, from banking fraud and investment scams to outright identity theft. We even have the online version of the Trojan horse myth, though, unfortunately, the virus version is more real than we'd like. We are surrounded by technologies of deception, some benign and some malicious. There may come a point which some may already have reached where the technological deception is so sophisticated and complete that we don't know what is real and what is not.

The Consequences of the Identity Theft Fear in the Sport Products Online Shopping From the Perspective of Physical Education Students

Abstract: Background. Today, online shopping has become one of the most important components of modern marketing that had both positive and negative consequences for customers. Objectives. The purpose of present research was to study the consequences of fear of identity theft in sport products online shopping from the perspective of physical education students. Methods. The present study is a descriptive-correlational survey and its statistical population includes all physical education students of Golestan province universities that 384 students were selected through available sampling as the statistical sample of the study. To collec research data, Hille et al (2015) fear of identity theft questionnaire, Chen et al (2015) perceived risk questionnaire and Chou & Hsu (2016) willingness to online shop questionnaire were used. Validity of the questionnaires was verified by 8 masters of sport management and internal consistency of questionnaires by using Cronbach's alpha was determined respectively 0.86, 0.78 and 0.81. To analyze the data and identify the effects of research variables, structural equation modeling was used in the PLS software. Results. The result showed that fear of losing money in the customer has a positive and significant effect on perceived risk. The effect of fear of credit damage in the customer on perceived risk was positive and significant. Finally, the results showed that the effect of perceived risk on the physical education students' willingness to online shopping was negative and significant. Conclusion. According to the results of the study, increasing awareness of physical education students about the selling rules of sports websites and increasing the security of sport products websites in order to reduce consumers' fears and concerns are suggested.

Towards a new model of management and securing digital identities

Abstract: The exponential growth of the web and the use of social networks in our area, gave birth to a new concept called digital identity, it's all digital traces that can be left in the internet such as photos and various comments. However, these digital identities are exposed to many dangers such as phishing, fraud, cyber-crime and identity theft. However, with an interconnected world, it is important to know with whom we communicate. Hence, the weightiness of digital identities' security becomes obvious. In this paper we propose a secure identification approach using a model of digital identity recognition. To do so, we will develop an architecture that can identify users based on a certain number of parameters, such as: federated digital identity management and certification of digital identity.

Avatar Facial Biometric Authentication Using Wavelet Local Binary Patterns

Abstract: Virtual worlds (e.g., Second Life) are populated by different types of people, businesses, and organizations. Users of virtual worlds, either individuals or organizations, might abuse the flexibility and adaptability offered by virtual environment by engaging in criminal activities. Even terrorist organizations have been active in virtual worlds. These organizations recently have used the virtual worlds for recruitment and to train their new members in an environment that is very similar to the real one. Since avatars are not just virtual creations as they have a great social and psychological correspondence with their creators, applying biometric techniques on avatars can give the law enforcement agencies and security experts the ability to identify who the actual users behind these avatars are. There is a mounting pressure to have techniques for verifying the real identities of the inhabitants of virtual worlds to secure cyberworld from incessant criminal activities (e.g., verbal harassment, fraud, money laundering, data or identity theft). In order to reduce the gap between our ability to recognizing human faces and avatar faces and to develop reliable tools for protecting virtual environments, we will discuss in this chapter how we can use different versions of local binary pattern (LBP) operators (traditional LBP, multi-scale LBP and hierarchical multi-scale LBP) to recognize avatar faces from two different virtual worlds (Second Life and Entropia Universe). This chapter includes a definition of discrete wavelet transform from a face recognition research perspective, a summary of previous work done on this topic, characteristics of the datasets used in the experiments as well as some suggestions for future work.

Modeling Access Environment and Behavior Sequence for Financial Identity Theft Detection in E-Commerce Services

Abstract: Online-to-Offline (O2O) e-commerce service platforms and their users are faced with various fraud risks. Among them, financial identity theft is a widely existing challenge. However, existing methods are insufficient to detect this type of fraud. In this paper, we address the financial identity theft detection problem in e-commerce services by leveraging access environment and behavior sequence. To explore the fraud patterns, we first make a detailed analysis using real cases of identity theft from Meituan, a leading O2O e-commerce platform in China. Our findings are twofold. First, fraudulent accounts sharing the same personal ID would have different access environments, such as devices and IP addresses. Second, a group of fraudulent accounts may have aggregations of devices, IP addresses, and delivery addresses. Based on these observations, we propose a hybrid method termed EnvIT to detect financial identity theft based on the heterogeneous graph and the behavior sequence. EnvIT is able to characterize the access environment and the historical behavior of the accounts. Furthermore, an attentive module is adopted to assign weights to different features automatically. We further evaluate EnvIT via extensive experiments using a real-world dataset from Meituan. Our experimental results demonstrate that EnvIt outperforms several baseline methods in fraudulent account detection and achieves an AUC of 0.9210.