Hanan Alossimi, Nouraalotaibi, Alhnouf alsubaie and Hanan Aljuaid, Princess Nourah Bint Abdul Rahman University, Saudi Arabia

Smishing, or SMS phishing, is a major global mobile security concern due to the lack of spam filtering in SMS. To address this, our project aimed to develop a smishing detection application for Arabic SMS messages. We created "Etiqa," an application utilizing a hybrid CNN-LSTM deep learning model, which achieved 98% accuracy in classifying Arabic SMS messages. The dataset was meticulously collected and processed with natural language analysis tools tailored for Arabic. The algorithm was implemented in Python, and the user interface, designed for Android, was developed using Dart on the Flutter framework. The interface was integrated with the model via Fast API. Looking ahead, we plan to enhance the system’s effectiveness and expand its capabilities.

Smishing , fraud, SMS, Detection, Artificial Intelligence