Enhanced Security and Reliability in Messaging Systems through Real-Time SMS Spam Filtering with Machine Learning

Enhanced Security and Reliability in Messaging Systems through Real-Time SMS Spam Filtering with Machine Learning

1Surabatthini Mounika ,2Uppala Ravi teja ,3Bala vijetha Reddy Badveli,4Sadhasivam Vamsy , 5Amanpreet singh

Author Affiliations

1, 2, 3, 4 School of Computer Application, Lovely Professional University, Jalandhar, Punjab, India

5Assistant Professor, School of Computer Application, Lovely Professional University, Jalandhar, Punjab, India

Author Emails

1 Corresponding author: surabatthini99999gmail.com

2 ravitejauppala77@gmail.com

3 vijethabadveli03@gmail.com

4 vamsysadhasivam@gmail.com

5 apsj24@gmail.com

Abstract— SMS spam has emerged as a major issue for cellular users, which leads to annoyance and inconvenience. Machine learning has been effective in filtering out spam SMS. Yet, applying these techniques in actual real-time situations poses special challenges. A newly published study seeks to tackle these challenges by building an efficient real-time. SMS spam filtering system based on machine learning. The main contribution of this work is to improve the performance of the system in real-time classification by focusing on data preparation, feature engineering, algorithm selection, and model deployment.

Keywords—SMS spam filtering, Real-time classification, Machine Learning