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Computing Platform Coverage via Light Host-based Intrusion Detection

Authors: Matthew Schmid;

Computing Platform Coverage via Light Host-based Intrusion Detection

Abstract

Abstract : Malicious software and hostile intrusions represent two of the largest threats to information systems today. During the course of this project we developed solutions that address both of these issues. The BayeScan prototype is a novel approach to detecting malicious software before it has a chance to strike. The AppID prototype provides a framework for the development of real-time host-based intrusion detection technology. The creation of these tools provides users with access to leading-edge research technologies in the fight against malicious software and malicious attackers.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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