Cybercrime victim forecasting and Prediction based on personality traits
Pro Research Analysisby
Searched over 200M research papers
Consensus Meter
Cybercrime Victim Forecasting and Prediction Based on Personality Traits
Introduction to Cybercrime and Personality Traits
Cybercrime has become a pervasive issue affecting individuals globally. Understanding the factors that contribute to cybercrime victimization is crucial for developing effective prevention strategies. Recent research has focused on the role of personality traits, particularly those outlined in the Big Five model, in predicting susceptibility to various forms of cybercrime.
Big Five Personality Traits and Cybercrime Victimization
General Victimization and Emotional Stability
Studies have shown that personality traits are generally associated with victimization, rather than being specific to cybercrime. Individuals with higher emotional stability are less likely to become victims of cybercrime compared to traditional crime . This suggests that emotional stability may provide a protective buffer against the stress and manipulation tactics often employed in cybercrimes.
Openness to Experience and Cyber-Enabled Crimes
Individuals scoring high on openness to experience are more susceptible to cyber-enabled crimes such as online intimidation, consumer fraud, and theft from bank accounts . This trait may make individuals more curious and willing to engage in online activities, increasing their exposure to potential threats.
Predictors of Cyber-Victimization and Cyber-Bullying
Adolescents and Personality Predictors
In adolescents, declining conscientiousness and increasing openness to new experiences and neuroticism are significant predictors of cyber-victimization. This age group is particularly vulnerable due to their developmental stage and frequent use of digital platforms.
Cyber-Bullying and Personality Traits
Cyber-bullying is predicted by traits such as callousness, impulsivity, and a lack of social skills. Victims of cyber-bullying often exhibit higher levels of empathy and psychological symptoms. These findings highlight the complex interplay between personality traits and online behaviors in predicting both victimization and perpetration of cyber-bullying.
Cyber-Fraud and Socio-Demographic Factors
Impulsivity and Sensation Seeking
Victims of cyber-fraud often exhibit high levels of impulsivity and sensation seeking. These traits, combined with frequent risky online activities, increase the likelihood of falling victim to scams. The distinction between one-off and repeat victims of cyber-fraud is minimal, indicating that these personality traits consistently predict susceptibility.
Age and Gender Differences
Older individuals and men are more likely to fall victim to investment scams, while women and less educated individuals are more susceptible to consumer scams. These socio-demographic factors, along with personality traits, provide a comprehensive profile of potential cyber-fraud victims.
Cybersecurity Behaviors and Risk-Taking
Risky Cybersecurity Behaviors
Personality traits and general risk-taking behaviors significantly predict insecure cybersecurity practices, such as using weak passwords and not logging out of shared accounts. Understanding these behaviors can help in developing targeted interventions to improve cybersecurity practices among high-risk individuals.
Ransomware Victimization
There is no compelling evidence to suggest that personality traits alone influence ransomware victimization. However, the aftermath of such attacks can be psychologically devastating, emphasizing the need for both technical and psychological support for victims.
Conclusion
Personality traits play a significant role in predicting cybercrime victimization. Traits such as emotional stability, openness to experience, impulsivity, and sensation seeking are particularly influential. By understanding these traits and their interactions with socio-demographic factors, we can develop more effective prevention and intervention strategies to mitigate the impact of cybercrime.
Sources and full results
Most relevant research papers on this topic