Abstract: Text messaging (SMS) remains widely used due to its simplicity and accessibility. However, its popularity has led to a rise in spam messages, including ads, scams, and phishing links.

This project implements a context-aware spam detection system using Python. Unlike naive filters, it does not assume unknown senders are scammers. Decisions are made using behavior-based scoring and ...

Circle to Search Update Adds Spam Detection; Google Brings Urgent Call Notes, New Emoji to Android Google's Circle to Search tool will now display an AI Overview with details sourced from the Web.

Spam is annoying and can sometimes be dangerous if it’s part of a widespread phishing attack. When you see spam, you delete it, at least that’s what conventional wisdom suggests. However, it now seems ...

This project implements a machine learning model to classify SMS messages as "spam" or "ham" (not spam) using Decision Trees and TF-IDF vectorization. CS_Project_II/ ├── dataset/ │ └── spam.csv # SMS ...

The Python Software Foundation warned users this week that threat actors are trying to steal their credentials in phishing attacks using a fake Python Package Index (PyPI) website. PyPI is a ...

Running Python scripts is one of the most common tasks in automation. However, managing dependencies across different systems can be challenging. That’s where Docker comes in. Docker lets you package ...