Year of Publication

2013

Degree Name

Master of Science (MS)

Document Type

Master's Thesis

College

Engineering

Department

Computer Science

First Advisor

Dr. Raphael A. Finkel

Abstract

I present RAACD, a software suite that detects misbehaving computers in large computing systems and presents information about those machines to the system administrator. I build this system using preexisting anomaly detection techniques. I evaluate my methods using simple synthesized data, real data containing coerced abnormal behavior, and real data containing naturally occurring abnormal behavior. I find that the system adequately detects abnormal behavior and significantly reduces the amount of uninteresting computer health data presented to a system administrator.

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