Development and testing of a methodology for diagnosing vulnerability to social engineering techniques based on L.N. Sobchik's individual-typological approach

Context and relevance. In the era of digitalization, with its high risk of personal data breaches on the Internet, people are increasingly becoming victims of cyber fraud based on social engineering techniques. Understanding which individual-typological personality traits predispose individuals to vulnerability to fraudsters is crucial for developing more effective counter-fraud strategies and improving cybersecurity overall. Objective. To develop, describe, and conduct initial testing of an original methodology for diagnosing individual vulnerability to social engineering techniques, based on L.N. Sobchik's theory of leading personality tendencies. Hypothesis. There is a statistically significant relationship between an individual's profile of leading personality tendencies (according to L.N. Sobchik) and their level of vulnerability to social engineering techniques. Methods and materials. The study involved 185 respondents aged 18 to 30 (M = 21.5, SD = 2.8; 68% female). Individual-typological personality traits were assessed using the L.N. Sobchik methodology, while vulnerability to social engineering was diagnosed using the developed author's methodology. Results. It was empirically confirmed that various configurations of personality tendencies lead to a specific vulnerability to certain manipulative techniques. Based on the research results, stable risk profiles were identified, confirming the construct validity and diagnostic value of the developed methodology for revealing “weak spots” in an individual's psychological defense. Conclusions. The developed methodology has demonstrated its diagnostic validity and opens up opportunities for transitioning to personalized information security awareness programs. The fundamental possibility and effectiveness of using L.N. Sobchik's individual-typological approach (theory of leading tendencies) for diagnosing vulnerability to social engineering has been confirmed: deep-seated personality characteristics are a significant predictor of behavior in situations of manipulative influence, which expands existing understanding of the nature of vulnerability in cybersecurity.