An AI Approach to Malware Similarity Analysis - Mapping the Malware Genome With a Deep Neural Network

Explore an innovative AI approach to malware similarity analysis using deep neural networks in this Black Hat conference talk. Delve into the challenges of traditional code sharing identification systems and discover how a new method leveraging deep learning can significantly improve accuracy and adaptability. Learn about the benefits of this approach, including reduced manual tuning, smaller deployment footprint, and increased effectiveness in identifying shared code relationships between malware samples. Understand how this system uses advanced features specifically designed for malware classification to achieve 98% accuracy. Gain insights into the workings of the method, its advantages over current approaches, and how it can be tailored to meet individual or organizational needs in cybersecurity.

Introduction
Why AI
The Fundamental Task
The Problem
The Question
The Perfect World
Why Use Deep Neural Networks
Variational AutoEncoder
Visualization
Conclusion