Botnet Detection on CTU-13 Using Lightweight Machine Learning Models

Botnets are among the most persistent cyber threats, enabling large-scale attacks such as spam, credential theft, and distributed denial-of-service DDoS. While deep learning approaches have recently been applied to botnet detection, they are computationally intensive and often lack...

AutoGraphAD: A Novel Approach Using Variational Graph Autoencoders for Anomalous Network Flow Detection

Network Intrusion Detection Systems NIDS are essential tools for detecting network attacks and intrusions. While extensive research has explored the use of supervised Machine Learning for attack detection and characterisation, these methods require accurately labelled datasets, which are very...

PT-2025-37241

Name of the Vulnerable Software and Affected Versions: Linux kernel affected versions not specified Description: A flaw exists in the Linux kernel related to PCI link speed calculation during retrain failures. Specifically, when pcie failed link retrain fails to retrain a link, it attempts to...