The psychological interaction of spam email features

Williams, Sarah E.; Sarno, Dawn M.; Lewis, Joanna; Shoss, Mindy K.; Neider, Mark; Bohil, Corey J.

doi:10.1080/00140139.2019.1614681

Cited by 5 publications

(5 citation statements)

References 19 publications

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“…The experiment was programmed and run in SR Research Ltd’s Experiment Builder. Stimuli were real emails, obtained from either the researcher’s inboxes/junk folders or web searches, and have been validated in previous studies (Sarno et al, 2020, Sarno et al, 2017; Patel et al, 2019; Williams et al, 2019). Participants had unlimited time to view the 100 emails.…”

Section: Methodsmentioning

confidence: 99%

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

Sarno

Neider

2021

Hum Factors

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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.

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Section: Methodsmentioning

confidence: 99%

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

Sarno

Neider

2021

Hum Factors

Self Cite

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“…e control and response of college students' psychological crisis are based on accurate identification and early warning [11]. e correlation and redundancy among the indicators of the early-warning model of psychological crisis is one of the effective methods to identify crisis signals and reduce crisis components [12].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Early-Warning Model of College Students’ Psychological Crisis Based on Characteristic Attribute

Chen

2022

Scientific Programming

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At present, the existing dynamic early-warning model of college students' psychological crisis cannot obtain psychological characteristics, and the error of psychological crisis prediction is large. The early-warning result of psychological crisis appears big deviation. A new dynamic early-warning model of college students' psychological crisis is designed based on characteristic attributes. In the process of modeling negative psychological crisis of college students, the fusion constraint fuzzy theory obtains the essence of college students' psychology from subjective and objective reasons, gives the different stages of college students' psychology, obtains the corresponding information entropy of the behavior hindrance in each stage of college students' psychology, and calculates the threshold value of the behavior tendency of college students' psychology. Based on the psychological state information of college students obtained by perception, the fuzzy comprehensive early-warning data model of feature attributes is constructed. According to the fuzzy comprehensive early-warning method and the early-warning index system, the early-warning factor set of college students' psychological crisis is constructed, and the dynamic early-warning model of college students' psychological crisis is constructed. Experimental results show that the mining results are consistent with the actual situation, and the grey relational degree, small error probability, and mean square ratio index are better than the present model.

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“…As a platform for online content publishing and dissemination, the network has brought new changes to people's social lives and communication methods. At the same time, the changes in human psychology and personality will be affected under the high-pressure working environment that will be displayed in the network social platform [1]. In order to better ensure national mental health, the design of the analysis model of the personality and psychological characteristics of the network users under the high-pressure working environment is proposed [2].…”

Section: Introductionmentioning

confidence: 99%

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

Yang

2022

Security and Communication Networks

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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.

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The psychological interaction of spam email features

Cited by 5 publications

References 19 publications

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

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

Dynamic Early-Warning Model of College Students’ Psychological Crisis Based on Characteristic Attribute

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

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