ENHANCING COMMUNICATION SECURITY THROUGH MACHINE LEARNING AND STREAMLIT
International Research Journal of Modernization in Engineering Technology and Science · 2024
The effectiveness of many machine learning methods for identifying spam in SMS and email interactions is examined in this study's abstract.Our study assesses each method's performance using Multinomial Naive Bayes, Random Forest, Support Vector Classifier, and Extra Tree Classifier.Preprocessing labelled datasets and extracting relevant features for model training are part of the study.Additionally, interaction with the Google Spreadsheet API and Google Drive API is implemented to help with real-time analysis and decision-making.Comprehensive testing and assessment are used to provide insights into the scalability, computational efficiency, and algorithm performance.The results further the progress of digital environment communication security and spam detection.