cyber attack modeling and simulation

Network attacks are increasingly complex and fast-evolving. A single attack may use multiple reconnaissance, exploit, and obfuscation techniques. This project investigates how to extract critical attack attributes, synthesize novel attack sequences, and reveal potential threats to critical assets in a timely manner. The project uses machine learning techniques to simultaneously identify new attack types and observed events that could identify those attacks.