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Social and Behavioral Sciences Commons

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Legal Studies

Bridgewater State University

International Journal of Cybersecurity Intelligence & Cybercrime

Fraud

Articles 1 - 2 of 2

Full-Text Articles in Social and Behavioral Sciences

“Elder Scam” Risk Profiles: Individual And Situational Factors Of Younger And Older Age Groups’ Fraud Victimization, Katalin Parti Nov 2022

“Elder Scam” Risk Profiles: Individual And Situational Factors Of Younger And Older Age Groups’ Fraud Victimization, Katalin Parti

International Journal of Cybersecurity Intelligence & Cybercrime

In an attempt to understand how differently fraud works depending on a victim’s age, we have examined the effects of situational (lifestyle-routine activities), self-control, and sociodemographic variables on scam victimization across age groups. The analysis was carried out on a national sample of 2,558 Americans, representative by age, sex, and race, and includes additional factors such as their education, living arrangement, employment, and propensity for reporting a crime or asking for help. The results substantiate research findings of the contribution of self-control and LRAT in predicting victimization in general but could not identify major situational and individual differences between older …


Dynamics Of Dark Web Financial Marketplaces: An Exploratory Study Of Underground Fraud And Scam Business, Bo Ra Jung, Kyung-Shick Choi, Claire Seungeun Lee Aug 2022

Dynamics Of Dark Web Financial Marketplaces: An Exploratory Study Of Underground Fraud And Scam Business, Bo Ra Jung, Kyung-Shick Choi, Claire Seungeun Lee

International Journal of Cybersecurity Intelligence & Cybercrime

The number of Dark Web financial marketplaces where Dark Web users and sellers actively trade illegal goods and services anonymously has been growing exponentially in recent years. The Dark Web has expanded illegal activities via selling various illicit products, from hacked credit cards to stolen crypto accounts. This study aims to delineate the characteristics of the Dark Web financial market and its scams. Data were derived from leading Dark Web financial websites, including Hidden Wiki, Onion List, and Dark Web Wiki, using Dark Web search engines. The study combines statistical analysis with thematic analysis of Dark Web content. Offering promotions …