Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/3456 2018 2018 Cybersecurity Department, Faculty of Science and Information Technology, Jadara University, Irbid, Jordan Nour Nour Cybersecurity Department, College of Computer Sciences and Informatics, Amman Arab University, Amman, Jordan Qusay Bsoul Faculty of Information Technology, Applied Science Private University, Amman, Jordan Ala Alzoubi Faculty of Engineering , Misr International University , cairo , Egypt Nardine T. Botros Faculty of Engineering , Misr International University , cairo , Egypt Moaz T. Fawzy MEU Research Unit, Middle East University, Amman, Jordan; Jadara Research Center, Jadara University, Irbid, Jordan Diaa Salama AbdElminaam College of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait Nour Mostafa This paper presents an optimized framework for detecting SMS spam using advanced machine learning algorithms and natural language processing (NLP) techniques. Two datasets, the Filtering Mobile Phone Spam Dataset and the SMS Spam Collection Dataset, were utilized to evaluate the performance of various classifiers, including Multinomial Naive Bayes, K-Nearest Neighbors, Support Vector Classifier, Decision Trees, and AdaBoost. The methodology encompasses comprehensive data preprocessing steps, such as tokenization, stopword removal, and text normalization, followed by feature extraction using TF-IDF and Bag-of-Words models. The classifiers’ performances were evaluated using accuracy, precision, recall, and F1-score, alongside cross-validation techniques. Results indicate that Support Vector Classifier and AdaBoost consistently achieved superior accuracy in distinguishing between spam and ham messages. The study underscores the importance of data preprocessing and model optimization in enhancing spam detection accuracy, offering valuable insights for improving SMS filtering systems in cybersecurity applications. 2025 2025 145 182 10.54216/FPA.180112 https://www.americaspg.com/articleinfo/3/show/3456