AIS RESEARCH

Artificial Intelligence Based Malware Analysis

Challenge

AIS employees present the Malware Analysis and Attributed using Genetic Information (MAAGI) system.

The underlying idea behind the MAAGI system is that there are strong similarities between malware behavior and biological organism behavior, and that applying biologically inspired methods to corpora of malware can help analysts better understand the ecosystem of malware attacks. Due to the sophistication of the malware and the analysis, the MAAGI system relies heavily on artificial intelligence techniques to provide this capability. It has already yielded promising results over its development life and will hopefully inspire more integration between the artificial intelligence and cyber–defense communities.

Key Insights:

This system takes advantage artificial intelligence advances over several decades to provide a comprehensive system for malware analysts to understand the past, present and future characteristics of malware
This system integrates artificial intelligence methods into a single system where various analyses use the results of other analyses to model, learn and predict characteristics of malware
The MAAGI system is expandable; new and intelligent methods to analyze malware will be incorporated into the system in the future, giving cyber–defenders a powerful and continually evolving tool to combat malware–based attacks

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