Dirk Ourston

Learn 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)
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)
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)
This paper presents a method for revising an approximate domain theory based on noisy data. The basic idea is to avoid making changes to the theory that account for only a small amount of data. This method is implemented in the EITHER propositional Horn-clause theory revision system. The paper presents empirical results on articially corrupted data to show(More)