Abstract

Online romance scams are a prevalent form of mass-marketing fraud in the West, and yet few studies have presented data-driven responses to this problem. In this type of scam, fraudsters craft fake profiles and manually interact with their victims. Due to the characteristics of this type of fraud, and the peculiarities of how dating sites operate, traditional detection methods (e.g., those used in spam filtering) are ineffective.

This talk will report on our investigation into the archetype of online dating profiles used in this form of fraud, including their use of demographics, profile descriptions, and images, shedding light on both the strategies deployed by scammers to appeal to victims and the implicit traits of victims themselves. Our work is presented in the context of building and evaluating a machine-learning classifier for detecting spam profiles, and elaborates on our findings from investigating areas of under-performance.