Exploring the Future Landscape: Emerging Trends in Social Engineering Defense

Abstract

Social engineering attacks exploit human behavior to bypass security measures, posing a growing threat in cybersecurity. This paper examines future defenses against these attacks by analyzing recent incidents and common attack vectors like phishing, pretexting, baiting, and tailgating, which leverage psychological manipulation. Key trends include AI and machine learning for real-time detection, and zero-trust architecture for stringent access controls and continuous identity verification. The development of regulatory frameworks and industry standards is also crucial for shaping effective defenses. As technology evolves, so do attack methods, necessitating comprehensive solutions that integrate technological, individual, organizational, and governmental strategies to safeguard society.