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The exponential growth of digital technologies has transformed the cybersecurity landscape, necessitating nuanced approaches to fostering cybersecurity awareness. Conventional education strategies, often uniform and standardized, inadequately address the cultural and demographic factors shaping online behaviors, particularly in diverse societal contexts like Kuwait (Abokhodair & Vieweg, 2016; Othman, 2023). Deeply rooted cultural values, such as family reputation and religious adherence, heavily influence individual perceptions and practices, underscoring the need for culturally adaptive frameworks that integrate technical knowledge with socio-cultural realities.
This study fills in that gap by using the protection motivation theory (PMT) as a base and adding cultural aspects to look at how threat perception, coping mechanisms, and social norms interact (Lie et al., 2021; Rippetoe & Rogers, 1987; Rogers, 1975). Advanced statistical methods, like K-means clustering and association rule mining (ARM), find patterns in people’s knowledge of cybersecurity and how they deal with problems (Abu et al., 2020; Agrawal et al., 1993). These insights help create a complete plan that uses gamification, microlearning, and scenario-based learning to help people change their behavior in a way that fits in with Kuwait’s culture.
Beyond addressing Kuwait’s specific needs, the proposed framework offers scalability and adaptability to other culturally diverse regions, providing a replicable model for enhancing global cybersecurity resilience.
This paper continues with “Cybersecurity Awareness and Cultural Context in Kuwait,” while “Theoretical Framework” reviews Kuwait’s national cybersecurity initiatives, providing a contextual background. “Technical Definitions” elaborates on the theoretical framework, integrating PMT with cultural dimensions. “Literature Review” defines key analytical concepts underpinning the hybrid model. “Data Collection and Description” details the methodology, including data collection and validation techniques. “Compliance” discusses the results and their implications for cybersecurity education. “The Hybrid Model” introduces a data-driven framework that combines K-means clustering and ARM to identify patterns in cybersecurity awareness and cultural sensitivity, enabling the development of targeted, culturally adaptive interventions. Finally, the “Conclusion” offers concluding insights and recommendations for future research, emphasizing the broader applicability of the proposed framework.