IEEE

Anomaly Detection in IoT Networks: A Deep Learning Approach Using Autoencoders

Abstract: The current fast proliferation of the Internet of Things (IoT) networks has made anomaly detection and security more difficult. Traditional methods are not able to detect hostile activities ...
IEEE

Context-Aware Natural Language Processing for Malware Detection

Abstract: As malware continues to evolve and cyber attacks become increasingly prevalent, it is critical to develop effective malware classification techniques for the detection and prevention of such ...
AFCEA

Robotics Researchers Take a Groundbreaking Approach to Land Mine Detection

Leaving behind a decades-long legacy of threats to life, land mines continue to be used across conflict zones and surrounding areas. Globally, the challenge remains immense. A 2024 NATO report notes ...
GitHub

Malware Detection using Deep Learning

This project uses deep learning techniques to detect malware by analyzing file characteristics, byte sequences, and behavioral patterns. It employs Convolutional Neural Networks (CNNs) for image-based ...
PC Gamer

This sneaky malware variant has been caught using fake Windows Update screens to trick users into installing info-stealing software themselves

If you're anything like me, you keep a sharp eye on your Windows Defender updates to make sure your PC is protected against the latest threats. However, while Defender is remarkably good at catching ...