Date of Award

12-17-2009

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Applied Science

First Advisor

Ningning Wu

Abstract

With the ability of modern system developers to develop intelligent programs that allows machines to learn, modify and evolve themselves, current trends of reactionary methods to detect and eradicate malicious software code from infected machines is proving to be too costly. Addressing malicious software after an attack is the current methodology and should be a fallback approach. A modern approach should be to perpetually monitor the "enterprise network backbone" traffic and broadcast alerts while taking protective and pre-emptive measures, in the event that the traffic falls out of the bounds of pre-described norms. This work demonstrates that a synergy approach of real-time monitoring of networking traffic collaborated with intra segmentation communications provide a more effective detection approach than the reactionary approach currently in use.

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