RTBTS: A Real-Time Behavioural Training System to Mitigate Psychological Vulnerabilities in Social Engineering Attacks

The aim of this research is to identify the psychological traits that make people susceptible to social engineering attacks and the effectiveness of current cybersecurity training. The study tries to identify how these factors can be better utilized to enhance the resilience of individuals in response to such an attack, due to a psychological or training deficiency. This involves data collection through structured surveying on internet platforms such as Google Forms. The analysis has been done by means of Python using statistical techniques, focusing on the descriptive analysis and regression analyses that set the links of psychological features and sensitivity to social engineering influenced by training programs. It followed from the research that certain psychological features of a person, like a high level of trust without its verification and readiness to conform with authority, raise his or her susceptibility to social engineering essentially. The training programs assessment had shown positive attitude to their helpfulness though deficiencies in adaptability and frequency of trainings reduce its potential to neutralize sophisticated social engineering techniques. These results reflect that, although the existing training is fairly successful, there is an urgent need for more flexible training methods that would consider individual psychological profiles and be updated regularly in combat with emerging social engineering strategies. Guided by these considerations above, this research supports the establishment of a Real-Time Behavioural Training System, RTBTS, continuous monitoring of dangers for dynamic adapted training modules.