Email Reading Behavior-Informed Machine Learning Model to Predict Phishing Susceptibility
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Springer Nature Singapore
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https://link.springer.com/content/pdf/10.1007/978-981-99-9785-5_40
Reference30 articles.
1. Alkhalil, Z., Hewage, C., Nawaf, L., Khan, I.: Phishing attacks: a recent comprehensive study and a new anatomy. Front. Comput. Sci. 3, 563060 (2021)
2. Aonzo, S., Merlo, A., Tavella, G., Fratantonio, Y.: Phishing attacks on modern android. In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, pp. 1788–1801, 2018
3. Arachchilage, N.A.G., Love, S.: A game design framework for avoiding phishing attacks. Comput. Hum. Behav. 29(3), 706–714 (2013)
4. Arachchilage, N.A.G., Love, S.: Security awareness of computer users: a phishing threat avoidance perspective. Comput. Hum. Behav. 38, 304–312 (2014)
5. Bednarik, R., Eivazi, S., Vrzakova, H.: A computational approach for prediction of problem-solving behavior using support vector machines and eye-tracking data. In: Nakano, Y.I., Conati, C., Bader, T. (eds.) Eye Gaze in Intelligent User Interfaces: Gaze-based Analyses, Models and Applications, pp. 111–134. Springer London, London (2013). https://doi.org/10.1007/978-1-4471-4784-8_7
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