Phishing attacks are among the most prevalent cyber threats, often leading to financial losses, reputational damage, and personal identity crises. This study investigates university students' behavior towards phishing attacks, focusing on the relationship between phishing Awareness and phishing avoidance behavior. Additionally, it examines the moderating effects of gender, age, and qualification on the use of anti-phishing tools, phishing avoidance behavior, and phishing Awareness. Data were collected from 715 university students through a structured questionnaire employing a quantitative approach. The results revealed a strong positive relationship between students' Awareness of phishing attacks and their phishing avoidance behavior. The mediation analysis showed that phishing awareness significantly mediates the relationship between using anti-phishing tools and phishing avoidance behavior. Furthermore, significant differences were observed in phishing Awareness, avoidance behavior, and the use of anti-phishing tools based on gender and age groups. These findings highlight the importance of tailored cybersecurity education programs considering these demographic factors to enhance students' resilience against phishing attacks. It is recommended to develop targeted cybersecurity education programs that focus on increasing phishing awareness and promoting the use of anti-phishing tools among university students, with particular emphasis on addressing demographic differences. The study's findings suggest that improving phishing awareness and tailoring interventions based on gender, age, and educational background can significantly enhance students' ability to avoid phishing attacks, strengthening cybersecurity resilience.

Phishing attacks are a significant threat to cybersecurity, particularly among university students who are frequent targets due to their extensive online activities and limited cybersecurity awareness. This study explores the impact of various factors, including threat susceptibility, phishing avoidance behavior, and the use of anti-phishing tools, on students' awareness of phishing attacks. Using a quantitative approach, data were collected from 715 university students worldwide through a structured questionnaire. The findings reveal that while students exhibit a moderate level of awareness about phishing attacks, their reliance on anti-phishing tools remains insufficient. The study identifies a significant positive relationship between the use of anti-phishing tools and increased phishing awareness and avoidance behaviors. Additionally, the research highlights the mediating role of anti-phishing tools in enhancing students' cybersecurity awareness. The results underscore the importance of integrating educational programs and advanced anti-phishing tools to improve students' resilience against phishing attacks. Recommendations for enhancing cybersecurity education and practices among university students are also provided.

This study presents a multi-agent framework for Arabic scam analysis, with roles for classification, behavioural interpretation and educational guidance. A total of 3000 messages were translated and enriched from English-language collections associated with the Short Message Service (SMS) Spam Collection, Enron and SmishTank. The experiments examine whether dataset-specific multilingual Text-to-Text Transfer Transformer (mT5) training improves classification and whether cultural annotations and an additional cultural training objective improve performance. The training, validation and test partitions contained 2400, 300 and 300 messages. Across ten random seeds, dataset-specific classifiers achieved 88.17% mean test accuracy and 88.07% macro-averaged F1 score (macro-F1); the 95% confidence interval for mean accuracy was 87.36–88.97%. Accuracy exceeded combined-data mT5 by 1.90 percentage points (Holm-adjusted $p=0.0250$). Mean accuracies were 98.50%, 92.90% and 73.10% for SMS, email and SmishTank-derived messages. In exploratory cultural comparisons, supplying annotations increased encoder–decoder accuracy by 1.80 points, while adding the cultural objective increased it by 1.23 points; neither difference was statistically significant after adjustment. The 150-message agent assessment yielded 84.7% mean integrated threat accuracy. The results support dataset-specific classification within the evaluated collections and show limited benefits from the tested cultural formulation. Independent Arabic data and user studies are priorities for extending the framework.