Published Paper Details:

The Intelligent SMS Spam Classifier is a Flask web tool that uses a Multinomial Naive Bayes model to spot and block spam messages. Text preprocessing through CountVectorizer lets the system find spam accurately while identifying regular messages. More sophisticated rules are required to handle the growing number of spam messages which use phishing and fraud tactics. The project improves how well machine learning can detect spam by making it more flexible across different environments. The easy-to-use Flask framework lets people use their phones or PCs to classify messages live. The system can detect spam patterns from different kinds of text through its training on a wide variety of SMS data. Our system reliability increases through security features which include input protection checks and HTTP data encryption plus constant incoming message speed management. The application provides flexibility to use either local resources or cloud services such as Heroku and AWS as its deployment platforms. The system will gain more capabilities through support for different languages along with deep learning technology and API-based filtering systems with a mobile app addition.