Yi Han, Shujiang Wu, Mengmeng Li, Zixi Wang, and Pengfei Sun (F5)

Online fraud has emerged as a formidable challenge in the digital age, presenting a serious threat to individuals and organizations worldwide. Characterized by its ever-evolving nature, this type of fraud capitalizes on the rapid development of Internet technologies and the increasing digitization of financial transactions. In this paper, we address the critical need to understand and combat online fraud by conducting an unprecedented analysis based on extensive real-world transaction data.

Our study involves a multi-angle, multi-platform examination of fraudsters' approaches, behaviors and intentions. The findings of our study are significant, offering detailed insights into the characteristics, patterns and methods of online fraudulent activities and providing a clear picture of the current landscape of digital deception. To the best of our knowledge, we are the first to conduct such large-scale measurements using industrial-level real-world online transaction data.

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Ke Coby Wang (Duke University), Michael K. Reiter (Duke University)

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Nina Shamsi (Northeastern University), Kaeshav Chandrasekar, Yan Long, Christopher Limbach (University of Michigan), Keith Rebello (Boeing), Kevin Fu (Northeastern University)

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A Preliminary Study on Using Large Language Models in...

Kumar Shashwat, Francis Hahn, Xinming Ou, Dmitry Goldgof, Jay Ligatti, Larrence Hall (University of South Florida), S. Raj Rajagoppalan (Resideo), Armin Ziaie Tabari (CipherArmor)

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Evaluating the Strength and Availability of Multilingual Passphrase Authentication

Chi-en Amy Tai (University of Waterloo), Urs Hengartner (University of Waterloo), Alexander Wong (University of Waterloo)

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