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Title:      IMPROVING PHISHING DETECTION VIA PSYCHOLOGICAL TRAIT SCORING
Author(s):      Sadat Shahriar, Arjun Mukherjee and Omprakash Gnawali
ISBN:      978-989-8704-40-5
Editors:      Piet Kommers and Mário Macedo
Year:      2022
Edition:      Single
Keywords:      Phishing, Email, BERT, Psychology
Type:      Full Paper
First Page:      131
Last Page:      139
Language:      English
Cover:      cover          
Full Contents:      click to dowload Download
Paper Abstract:      Phishing emails exhibit some unique psychological traits which are not present in legitimate emails. From empirical analysis and previous research, we find three psychological traits most dominant in Phishing emails - A Sense of Urgency, Inducing Fear by Threatening, and Enticement with Desire. We manually label 10% of all phishing emails in our training dataset for these three traits. We leverage that knowledge by training BERT, Sentence-BERT (SBERT), and Character-level-CNN models and capturing the nuances via the last layers that form the Phishing Psychological Trait (PPT) scores. For the phishing email detection task, we use the pretrained BERT and SBERT model, and concatenate the PPT scores to feed into a fully-connected neural network model. Our results show that the addition of PPT scores improves the model performance significantly, thus indicating the effectiveness of PPT scores in capturing the psychological nuances. Furthermore, to mitigate the effect of the imbalanced training dataset, we use the GPT-2 model to generate phishing emails (Radford et al., 2019. Our best model outperforms the current State-of-the-Art (SOTA) model's F1-score by 4.54%. Additionally, our analysis of individual PPTs suggests that Fear provides the strongest cue in detecting phishing emails.
   

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