Biblio
{Phishing is a social engineering tactic used to trick people into revealing personal information [Zielinska, Tembe, Hong, Ge, Murphy-Hill, & Mayhorn 2014]. As phishing emails continue to infiltrate users' mailboxes, what social engineering techniques are the phishers using to successfully persuade victims into releasing sensitive information? Cialdini's [2007] six principles of persuasion (authority, social proof, liking/similarity, commitment/consistency, scarcity, and reciprocation) have been linked to elements of phishing emails [Akbar 2014; Ferreira, & Lenzini 2015]; however, the findings have been conflicting. Authority and scarcity were found as the most common persuasion principles in 207 emails obtained from a Netherlands database [Akbar 2014], while liking/similarity was the most common principle in 52 personal emails available in Luxemborg and England [Ferreira et al. 2015]. The purpose of this study was to examine the persuasion principles present in emails available in the United States over a period of five years. Two reviewers assessed eight hundred eighty-seven phishing emails from Arizona State University, Brown University, and Cornell University for Cialdini's six principles of persuasion. Each email was evaluated using a questionnaire adapted from the Ferreira et al. [2015] study. There was an average agreement of 87% per item between the two raters. Spearman's Rho correlations were used to compare email characteristics over time. During the five year period under consideration (2010–2015), the persuasion principles of commitment/consistency and scarcity have increased over time, while the principles of reciprocation and social proof have decreased over time. Authority and liking/similarity revealed mixed results with certain characteristics increasing and others decreasing. The commitment/consistency principle could be seen in the increase of emails referring to elements outside the email to look more reliable, such as Google Docs or Adobe Reader (rs(850) = .12
Phishing is a social engineering tactic used to trick people into revealing personal information [Zielinska, Tembe, Hong, Ge, Murphy-Hill, & Mayhorn 2014]. As phishing emails continue to infiltrate users' mailboxes, what social engineering techniques are the phishers using to successfully persuade victims into releasing sensitive information?
Cialdini's [2007] six principles of persuasion (authority, social proof, liking/similarity, commitment/consistency, scarcity, and reciprocation) have been linked to elements of phishing emails [Akbar 2014; Ferreira, & Lenzini 2015]; however, the findings have been conflicting. Authority and scarcity were found as the most common persuasion principles in 207 emails obtained from a Netherlands database [Akbar 2014], while liking/similarity was the most common principle in 52 personal emails available in Luxemborg and England [Ferreira et al. 2015]. The purpose of this study was to examine the persuasion principles present in emails available in the United States over a period of five years.
Two reviewers assessed eight hundred eighty-seven phishing emails from Arizona State University, Brown University, and Cornell University for Cialdini's six principles of persuasion. Each email was evaluated using a questionnaire adapted from the Ferreira et al. [2015] study. There was an average agreement of 87% per item between the two raters.
Spearman's Rho correlations were used to compare email characteristics over time. During the five year period under consideration (2010--2015), the persuasion principles of commitment/consistency and scarcity have increased over time, while the principles of reciprocation and social proof have decreased over time. Authority and liking/similarity revealed mixed results with certain characteristics increasing and others decreasing.
The commitment/consistency principle could be seen in the increase of emails referring to elements outside the email to look more reliable, such as Google Docs or Adobe Reader (rs(850) = .12, p =.001), while the scarcity principle could be seen in urgent elements that could encourage users to act quickly and may have had success in eliciting a response from users (rs(850) = .09, p =.01). Reciprocation elements, such as a requested reply, decreased over time (rs(850) = -.12, p =.001). Additionally, the social proof principle present in emails by referring to actions performed by other users also decreased (rs(850) = -.10, p =.01).
Two persuasion principles exhibited both an increase and decrease in their presence in emails over time: authority and liking/similarity. These principles could increase phishing rate success if used appropriately, but could also raise suspicions in users and decrease compliance if used incorrectly. Specifically, the source of the email, which corresponds to the authority principle, displayed an increase over time in educational institutes (rs(850) = .21, p <.001), but a decrease in financial institutions (rs(850) = -.18, p <.001). Similarly, the liking/similarity principle revealed an increase over time of logos present in emails (rs(850) = .18, p <.001) and decrease in service details, such as payment information (rs(850) = -.16, p <.001).
The results from this study offer a different perspective regarding phishing. Previous research has focused on the user aspect; however, few studies have examined the phisher perspective and the social psychological techniques they are implementing. Additionally, they have yet to look at the success of the social psychology techniques. Results from this study can be used to help to predict future trends and inform training programs, as well as machine learning programs used to identify phishing messages.
One hundred-sixty four participants from the United States, India and China completed a survey designed to assess past phishing experiences and whether they engaged in certain online safety practices (e.g., reading a privacy policy). The study investigated participants' reported agreement regarding the characteristics of phishing attacks, types of media where phishing occurs and the consequences of phishing. A multivariate analysis of covariance indicated that there were significant differences in agreement regarding phishing characteristics, phishing consequences and types of media where phishing occurs for these three nationalities. Chronological age and education did not influence the agreement ratings; therefore, the samples were demographically equivalent with regards to these variables. A logistic regression analysis was conducted to analyze the categorical variables and nationality data. Results based on self-report data indicated that (1) Indians were more likely to be phished than Americans, (2) Americans took protective actions more frequently than Indians by destroying old documents, and (3) Americans were more likely to notice the "padlock" security icon than either Indian or Chinese respondents. The potential implications of these results are discussed in terms of designing culturally sensitive anti-phishing solutions.
Phishing is a social engineering tactic that targets internet users in an attempt to trick them into divulging personal information. When opening an email, users are faced with the decision of determining if an email is legitimate or an attempt at phishing. Although software has been developed to assist the user, studies have shown they are not foolproof, leaving the user vulnerable. Multiple training programs have been developed to educate users in their efforts to make informed decisions; however, training that conveys the real world consequences of phishing or training that increases a user’s fear level have not been developed. Conveying real world consequences of a situation and increasing a user’s fear level have been proven to enhance the effects of training in other fields. Ninety-six participants were recruited and randomly assigned to training programs with phishing consequences, training programs designed to increase fear, or a control group. Preliminary results indicate that training helped users identify phishing emails; however, little difference was seen among the three groups. Future analysis will include a factor analysis of personality and individual differences that influence training efficacy.