Enhanced Security and Reliability in Messaging Systems through Real-Time SMS Spam Filtering with Machine Learning
Year: 2025
Type: article
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
DOI: 10.55041/ijsrem48995
Author: Surabatthini Mounika
Language: English
Topic: Spam and Phishing Detection
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4410938435