Social engineering attacks pose a growing threat to individuals, organizations, and society at large, exploiting human psychology to manipulate victims into divulging sensitive information or taking harmful actions. This research paper presents a comprehensive study on the development and implementation of AI-based solutions for the detection and mitigation of social engineering attacks. Leveraging machine learning algorithms, natural language processing techniques, and behavioural analysis, our proposed system aims to enhance the security posture of digital ecosystems. We discuss the design, training, and evaluation of the AI model, which exhibits promising results in identifying deceptive social engineering attempts. Furthermore, we explore real-world applications and potential challenges in deploying such technology. The findings highlight the crucial role of AI in bolstering cybersecurity defences and underline the importance of continued research in countering evolving social engineering tactics.
AI, Social Engineering, Machine Learning, Cybersecurity, Phishing Detection