Abstract
Being able to identify likely trends is the core of building better countermeasures. This chapter describes a light-weight approach to identifying differences in user vulnerabilities. That allows us to quantify vulnerabilities before they are actively abused. By being able to anticipate what fraudsters will be likely to do eventually, it is possible to build countermeasures that address big open vulnerabilities.
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V. Anandpara, A. Dingman, M. Jakobsson, D. Liu, H. Roinestad, Phishing IQ tests measure fear, not ability, in Proceedings of 11th International Conference on Financial Cryptography and Data Security (2007), pp. 362–366
M. Jakobsson, T.-F. Yen, How vulnerable are we to scams? in BlackHat (2015)
M. Jakobsson, N. Johnson, P. Finn, Why and how to perform fraud experiments. IEEE Secur. Priv. 6 (2), 66–68 (2008)
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Yen, TF., Jakobsson, M. (2016). Predicting Trends. In: Jakobsson, M. (eds) Understanding Social Engineering Based Scams. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-6457-4_3
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DOI: https://doi.org/10.1007/978-1-4939-6457-4_3
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4939-6455-0
Online ISBN: 978-1-4939-6457-4
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