Abstract
This chapter focuses on the taxonomy of scam emails collected from various sources and investigates long-term trends in scam emails. We first describe a large-scale compendium of scam emails collected from various sources, and then present an analysis regarding what kind of scams exist, what their structures are, and how they are related to each other. We then describe a machine learning classifier built based upon the taxonomy analysis, and use it to cluster scam emails into major scam categories. Then an analysis of different trends from each scam category is presented. Our analysis shows a clear trend that spam-like non-targeted scams are decreasing continuously while targeted scams with specific victims have been getting more prevalent over the last 10 years.
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Notes
- 1.
Oddly, to scammers, it is not people who are entered in lotteries, but email addresses. Correspondingly, email addresses, not their owners, are the winners of the lotteries.
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McCoy, D., Park, Y., Shi, E., Jakobsson, M. (2016). Identifying Scams and Trends. In: Jakobsson, M. (eds) Understanding Social Engineering Based Scams. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-6457-4_2
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DOI: https://doi.org/10.1007/978-1-4939-6457-4_2
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