Integrating Sociocultural Intelligence Into Cybersecurity: A LESCANT-Based Approach for Phishing and Social Engineering Detection

The study explored the impact of sociocultural nuances in annotated datasets on improving cybersecurity systems, particularly to mitigate phishing and social engineering threats. It proposes strategies to expand the diversity of the dataset through global partnerships, develop adaptive detection models capable of learning sociocultural patterns in real time, and investigate automated annotation techniques to reduce cultural biases. A novel adaptation of the LESCANT framework for phishing analysis was formalized, allowing comprehensive detection strategies. This study provides mathematical models, Python implementations, and visualizations, supported by examples from various regions, to demonstrate the efficacy of these methodologies. Future directions include integrating sociocultural dimensions into broader cybersecurity applications.