The year opened without a reset. The same pressure carried over, and in some places it tightened. Systems people assume are boring or stable are showing up in the wrong places. Attacks moved quietly, ...

If there’s one universal experience with AI-powered code development tools, it’s how they feel like magic until they don’t. One moment, you’re watching an AI agent slurp up your codebase and deliver a ...

Abstract: Caller ID spoofing (CIS) remains a major challenge in combating spam calls, as attackers may generate spam even with seemingly legitimate identifiers. Existing CIS detection (CISD) ...

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 ...

They look, move and even smell like the kind of furry Everglades marsh rabbit a Burmese python would love to eat. But these bunnies are robots meant to lure the giant invasive snakes out of their ...

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 ...