Machine Learning for Enhanced Malware Detection and Classification

Explore a groundbreaking framework for enhanced malware detection and classification using machine learning in this 29-minute SANS DFIR Summit 2024 talk. Delve into the challenges posed by the increasing prevalence and sophistication of malware, with VirusTotal reporting over 2 million daily submissions. Learn how artificial intelligence can bolster cybersecurity efforts where traditional detection mechanisms fall short. Discover a novel Ensemble Classification Facility that leverages multiple machine learning models to improve malware classification. Gain insights from the first-known research utilizing machine learning to classify an entire 200+ gigabyte malware family corpus, comprising over 80,000 unique samples across 70+ malware families. Explore newly released labeled datasets for future malware classification efforts. Understand the potential of integrating artificial intelligence into automated malware analysis and how it can revolutionize the fight against evolving cyber threats.

Machine Learning for Enhanced Malware Detection & Classification