The psychological interaction of spam email features

So Many Phish, So Little Time: Exploring Email Task Factors and Phishing Susceptibility

OBJECTIVE

The present studies examine how task factors (e.g., email load, phishing prevalence) influence email performance.

BACKGROUND

Phishing emails are a paramount cybersecurity threat for the modern email user. Research attempting to understand how users are susceptible to phishing attacks has been limited and has not fully explored how task factors (e.g., prevalence, email load) influence accurate detection.

METHOD

In three experiments, participants classified emails as either legitimate or not legitimate and reported on a variety of other categorizations. The first two experiments examined how email load and phishing prevalence influence phishing detection independently. The third experiment examined the interaction of these two factors to determine whether they have compounding effects. All three experiments utilized individual difference variables to examine how cognitive, behavioral, and personality factors may influence classifications.

RESULTS

Experiment 1 suggests that high email load can make the task appear more challenging. Experiment 2 indicates that low phishing prevalence can decrease sensitivity for phishing emails. Experiment 3 demonstrates that high levels of email load can decrease classification accuracy under 50/50 prevalence rates. Notably, performance was poor across all experiments, with phishing detection near chance levels and low discriminability for emails. Participants demonstrated poor metacognition with over confidence, low self-reported difficulty, and low perceived threat for the emails.

CONCLUSION

Overall, the present studies suggest that high email load and low phishing prevalence can influence email classifications.

APPLICATION

Organizations and researchers should consider the influences of both email load and phishing prevalence when implementing phishing interventions.

Analysis Model of Personality and Psychological Characteristics of Network Users under High-Pressure Working Environment

Based on the prediction of social network psychological indicators, this paper studies the analysis model of network users’ personality and psychological characteristics under a high-pressure working environment. Through the analysis of five common network users’ personalities, the characteristics of personality psychology are extracted. Combined with the high-pressure working environment, this paper analyzes the characteristics of network users’ personalities and psychology, collects the characteristics of network users’ personality themes, and analyzes the characteristics of the dynamic extended dictionary. In order to ensure the accuracy of feature analysis, the author’s LDA algorithm is used to predict the network short text psychological index of network users under a high-pressure working environment. The experimental results show that the model designed in this paper is better than the traditional method in practical application.