Cybersecurity threats have been growing significantly in both volume and sophistication over the past decade. This poses great challenges to malware detection without considerable automation. In this paper, we have proposed a novel approach by extending our recently suggested artificial neural network (ANN)- based model with feature selection using the principal component analysis (PCA) technique for malware detection.

The trend toward active, targeted attacks continues to grow in prominence. Matrix is the latest malware to use these tactics. In this report, SophosLabs takes a deeper look at this low-key, developing ransomware threat.

Victories against cybercrime demand radical change to defense.

Due to the popularity of portable document format (PDF) and the increasing number of vulnerabilities in major PDF viewer applications, malware writers continue to use the format to deliver malware via web downloads, email attachments, and other methods in both targeted and non-targeted attacks. The topic of how to effectively block malicious PDF documents has received a huge amount of research interests in both cybersecurity industry and academia with no sign of slowing down.

An in-depth peek into the VM running in modern web browsers.

So what exactly is an adversarial autoencoder, and why might you want to use one? They are a clever idea leading to a flexible and general framework for a lot of interesting tasks. Take a deeper dive into AAEs in this paper.