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George Webster

Mr. George Webster



Research Interests

My primary research focus aims to address the cognitive bias in cyber defense, specifically in developing scalable methods to perform cyber analytics. My academic and work background is centered in Virtual Machine Introspection, static analysis techniques, distributed systems, and the psychology of cyber criminals.


Supervised Work



2017 Finding the Needle: A Study of the PE32 Rich Header and Respective Malware Triage
Empowering Convolutional Networks for Malware Classification and Analysis
Size Matters: Open-Source Framework for Large Scale Analysis
From Mole Hills to Mountains: Revealing Rich Header and Malware Triage
2016 Deep Learning for Classification of Malware System Call Sequences
A Study of the Rich Header and Respective Malware Triage
SKALD: A Scalable Architecture for Feature Extraction, Multi-User Analysis, and Real-Time Information Sharing
Adaptive Semantics-Aware Malware Classification
2015 Internet-Scale File Analysis
2014 Pitfalls of virtual machine introspection on modern hardware
Scalability, Fidelity and Stealth in the DRAKVUF Dynamic Malware Analysis System