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This paper describes a novel approach using Hidden Markov Models (HMM) to detect complex Internet attacks. These attacks consist of several steps that may occur over an extended period of time. Within each step, specific actions may be interchangeable. A perpetrator may deliberately use a choice of actions within a step to mask the intrusion. In other(More)
in KBANN (which translates a theory into a neural-net, renes it using backpropagation, and then retranslates the result back into rules) by adding extra hidden units and connections to the initial network; however, this would require predetermining the number and type of intermediate concepts to be created. In addition, unlike EITHER, KBANN is not(More)
Ourston, D. and R. This article describes a comprehensive system for automatic theory (knowledge base) refinement. The system applies to classification tasks employing a propositional Horn-clause domain theory. Given an imperfect domain theory and a set of training examples, the approach uses partial and incorrect proofs to identify potentially faulty(More)
Austin Info Systems (AIS) is developing the Open Source Automated Link Analysis Tool (OSALAT), an application that uses ontologies to help search open source repositories and processes the search results. The use of ontologies has greatly benefited OSALAT in a variety of ways, including the decoding the information contained within the open source(More)