Adversarial Debiasing of Machine Learning Models for Enhanced Network Security against DDoS Attacks

Distributed Denial of Service attacks are a growing threat to network infrastructure, and new techniques, including the use of generative AI, make them harder to detect. Traditional detection systems, such as rule based firewalls, often fail to identify these evolving attack patterns. In this...

Improving the Identification of Real-World Malware's DNS Covert Channels Using Locality Sensitive Hashing

Nowadays, malware increasingly uses DNS-based covert channels in order to evade detection and maintain stealthy communication with its command-and-control servers. While prior work has focused on detecting such activity, identifying specific malware families and their behaviors from captured...

DroidDetective - A Machine Learning Malware Analysis Framework For Android Apps

A machine learning malware analysis framework for Android apps. DroidDetective is a Python tool for analysing Android applications APKs for potential malware related behaviour and configurations. When provided with a path to an application APK file Droid Detective will make a prediction using it'...