Coordinated Machine Learning-Based Vulnerability & Security Patching for Resilient Virtual Computing Infrastructure

PI(s), Co-PI(s), Researchers:

PI: Helen Gu; Researchers: Olufogorehan Tunde-Onadele (Fogo)

HARD PROBLEM(S) ADDRESSED
This refers to Hard Problems, released November 2012.

Resilient Architectures

Our research aims at aiding administrators of virtualized computing infrastructures in making services more resilient to security attacks through applying machine learning to reduce both security and functionality risks in software patching by continually monitoring patched and unpatched software to discover vulnerabilities and triggering proper security updates.

PUBLICATIONS
Papers written as a result of your research from the current quarter only.

KEY HIGHLIGHTS

We focused on enhancing the accuracy of our security bug detection schemes by evaluating different filtering schemes. We also introduced ranking algorithms to provide ranked list of vulnerable functions out of millions of functions in modern server systems. We see that our algorithms can identify true vulnerable functions within top ranked functions.

COMMUNITY ENGAGEMENTS

EDUCATIONAL ADVANCES: