Nature

Mobile malware detection method using improved GhostNetV2 with image enhancement technique

In recent years, image-based feature extraction and deep learning classification methods are widely used in the field of malware detection, which helps improve the efficiency of automatic malicious ...
Nature

Scalable architecture for autonomous malware detection and defense in software-defined networks using federated learning approaches

This paper proposes a scalable and autonomous malware detection and defence architecture in software-defined networks (SDNs) that employs federated learning (FL). This architecture combines SDN’s ...
Opinion
Security BoulevardOpinion

When Malware Becomes Unique on Every Machine, Detection Stops Being a Strategy

The worm that writes its own attack for every machine it encounters is not a warning about what is coming. It is a demonstration of what is already here. The question is whether the industry's ...
Dark Reading

Antivirus, Anti-Malware Lead Demand for AI/ML Tools

Artificial intelligence (AI) and machine learning (ML) tools are gaining traction in enterprises, and the rate of adoption is particularly notable in cybersecurity operations, where these technologies ...
Infosecurity-magazine.com

Malicious Machine Learning Model Attack Discovered on PyPI

A new campaign exploiting machine learning (ML) models via the Python Package Index (PyPI) has been observed by cybersecurity researchers. ReversingLabs said threat actors are using the Pickle file ...