Phishing attacks are a common tool used by malicious actors to gain access to systems or exploit individuals. Much of the phishing detection schemes focuses on awareness training programs and detection models. While these methods, detection models utilizing machine learning techniques, blacklists, and other email characteristics such as domain names, email addresses, and URLs are helpful in combating the problem, more research is needed in order to detect phishing scams more accurately and precisely where phishing email data can play an important role. Nowadays phishing attacks exploit human vulnerabilities by targeting specific human emotions, such as fear, to trick users into giving up their personal information. Consideration of the emotional exploitation present in phishing emails data combined with current detection schemes could lead to better detection. The goal of this paper is to analyze the emotional related content of a phishing email dataset to see if there is any relation between the emotion exploited and the sender’s email domain. In addition, this research demonstrates the need for the collection and analysis of the various types of phishing emails and its related emotional content that can be beneficial in developing better detection methods.
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