Evaluating Phishing Awareness Strategies: A Comparative Study of Education-based approaches and Game-based learning

This paper investigates the effectiveness of phishing awareness methods amidst the rising tide of cyberattacks. A quantitative analysis of 115 participants was conducted to assess individual vulnerability to phishing and evaluate the impact of various awareness strategies. Descriptive and inferential statistics were used to explore the influence of demographic variables on susceptibility to phishing. The findings indicate that traditional courses and interactive games are beneficial but require continuous re-evaluation. Machine learning models, including Logistic Regression and Random Forest, were developed based on these findings to predict phishing vulnerability. The analysis highlights the importance of age and field of activity in predicting vulnerability, while gender shows a less significant impact. This research underscores the shortcomings of current approaches and suggests improvements for more inclusive and adaptive strategies to counter evolving phishing threats. Future research should explore real user behaviors influenced by psychological factors and ensure balanced participant distribution to enhance the understanding of phishing vulnerability and defense mechanisms.