A new variation of the fake recruiter campaign from North Korean threat actors is targeting JavaScript and Python developers ...

Python libraries handle real business tasks like APIs, data analysis, and machine learning at scaleUsing ready-made libraries reduces coding erro ...

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 ...

LITTLE ROCK, Ark. - Arkansas work zone cameras will now be able to detect when drivers are on their cell phone or other handheld devices, the state Department of Transportation (ARDOT) announced ...

Researchers at Google’s Threat Intelligence Group (GTIG) have discovered that hackers are creating malware that can harness the power of large language models (LLMs) to rewrite itself on the fly. An ...

Threat actors with ties to the Democratic People's Republic of Korea (aka DPRK or North Korea) have been observed leveraging ClickFix-style lures to deliver a known malware called BeaverTail 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 ...

Abstract: Mobile Telecom subscriber’s are interrupted by these spams and it becomes necessary for the service providers to take steps to protect the user. In this project, we aim toward developing an ...

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 ...

Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle with ...