An Enhanced Machine Learning with NLP Modelling Technique for Smishing Attacks Detection in Low-Resourced Languages

Abstract

Smishing, a form of phishing through SMS, has emerged as a significant cybersecurity threat, particularly on mobile money platforms in regions with limited cybersecurity awareness. This research introduces a robust machine learning model integrated with advanced natural language processing (NLP) techniques for effective smishing detection. The proposed model targets English and Bemba, a low-resourced language, addressing a critical gap in cybersecurity research for inguistically diverse, resource-constrained environments.