A Target-Centric Ontology for Intrusion Detection

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Author's Abstract

We have produced an ontology specifying a model of computer attacks. Our ontology is based upon an analysis of over 4,000 classes of computer intrusions and their corresponding attack strategies and is categorized according to: system component targeted, means of attack, consequence of attack and location of attacker. We argue that any taxonomic characteristics used to define a computer attack be limited in scope to those features that are observable and measurable at the target of the attack. We present our model as a target-centric ontology that is to be refined and expanded over time. We state the benefits of forgoing dependence upon taxonomies, in favor of ontologies, for the classification of computer attacks and intrusions. We have specified our ontology using DAML+OIL and have prototyped it using DAMLJessKB. We present our model as a target-centric ontology and illustrate the benefits of utilizing an ontology in lieu of a taxonomy, by presenting a use case scenario of a distributed intrusion detection system.

Resource: http://meritology.com/library/public/A%20Target-Centric%20Ontology%20for%20Intrusion%20Detection.pdf Author: John Pinkston, Jeffrey Undercoffer, Anupam Joshi and Timothy Finin Title: A Target-Centric Ontology for Intrusion Detection

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