In an era marked by increasing cyber threats, understanding the human factors that influence security perceptions is more crucial than ever. As cyber risks, particularly those stemming from insider behavior and intricate attack strategies, become increasingly common, this research highlights several key issues including the limitations of current detection systems that primarily focus on technological solutions; the tendency to overlook the critical role of human behavior in cybersecurity; and the urgent need for strategies that integrate behavioral insights to enhance threat mitigation. By analyzing insider threat dataset, we reveal important correlations between personality traits and the suspicion of cyber threats, suggesting that understanding these traits is essential for evaluating vulnerabilities. Our findings indicate that incorporating human behavior insights into sophisticated deep learning models can significantly enhance CyberSecurity strategies, promoting a more comprehensive, human-oriented approach to threat identification and management. This paper not only elucidates the vital connections between personality traits and CyberSecurity vulnerabilities but also proposes an innovative framework for blending psychometric data with conventional intrusion detection systems.