Defending against smishing attacks: State-of-the-art techniques, challenges, limitations, and future directions

Smishing is a hostile operation by attackers to get sensitive information using misrepresentation. Because autonomous anti-phishing systems are not very accurate, they may miss smishing crimes that are facilitated by thoughtful phishing SMS, or short message Smishing attacks have become more common over the past few years because of the widespread adoption of these user-friendly and useful devices. The goal of this literature review is to investigate the approaches and strategies employed in smishing attacks by utilizing categorization methods. This article outlines the current systems that employ deep learning and machine learning methods, along with their advantages, disadvantages, and restrictions. To effectively prevent spam messages rather than detect them, this study discusses the potential for future advancements in processing natural languages. We figured out about psychological issues, argumentation and need, bias against confirmation, and ignorance, among other smishing-related insights, problems, and future research directions. These findings suggest that understanding the cognitive process and its workings is essential to developing solutions for smishing attack detection and mitigation.