说服
网络钓鱼
计算机科学
精化可能性模型
心理学
社会心理学
万维网
互联网
作者
Rohit Valecha,Pranali Mandaokar,H. Raghav Rao
标识
DOI:10.1109/tdsc.2021.3118931
摘要
Phishing is an attempt to acquire sensitive information from an unsuspecting victim by malicious means. Recent studies have shown that phishers often use persuasion techniques to get positive responses from the recipients. Still missing from this literature are studies assessing effectiveness of persuasion cues in phishing email detection. Specifically focusing on gain and loss persuasion cues, we address the following research questions: In detecting phishing emails, (1) how effective are the gain persuasion cues, (2) how effective are the loss persuasion cues, and (3) how effective is an integrated model of gain and loss persuasion In order to address the research questions, we create three machine learning models, with relevant gain persuasion cues, loss persuasion cues, and combined gain and loss persuasion cues respectively, and compare the estimates with a baseline model that does not account for the persuasion cues. The results show that the three phishing detection models with relevant persuasion cues significantly outperform the baseline model by approximately 5% to 20% percent in terms of F-score, thus representing reliable methods for phishing email detection.
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