Abstract:
The rapid advancement of artificial intelligence (AI) has introduced complex
cyberthreats such as deepfake scams, AI-generated phishing, and adaptive malware,
which are harder to detect than traditional attacks. Sri Lankan university
undergraduates, who rely heavily on digital technologies, are increasingly vulnerable
due to limited awareness and readiness. This study investigates how AI-driven threats
influence students’ motivation to adopt protective cybersecurity behaviors, guided by
the Protection Motivation Theory (PMT). It examines five psychological constructs:
Self-Efficacy in Handling AI Threats, Perceived Vulnerability to AI Threats,
Perceived AI Threat Severity, Cybersecurity Knowledge of AI Threat, and Response
Efficacy toward AI Threats. Using a quantitative design, data were gathered from 384
students across 17 state universities through a structured questionnaire and quota
sampling. Statistical analysis via SPSS confirmed strong reliability (Cronbach’s α >
0.70) and validity (KMO = 0.873, p < 0.001). Correlation results showed significant
positive relationships between all constructs and protection motivation (r = 0.68–
0.78, p < 0.01). Regression results indicated that the model explained 72% of the
variance (R² = 0.72), with Response Efficacy as the strongest predictor (β = 0.284, p
< 0.001). The findings emphasize the importance of strengthening students’
confidence, awareness, and belief in effective cybersecurity measures. Outcomes are
expected to benefit universities, educators, policymakers, and industry stakeholders
by guiding targeted awareness programs, curriculum reforms, and institutional
policies that enhance digital resilience against AI-driven threats.
