Browsing by Author "Williams, Lloyd Carter"

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    Augmentation of Intrusion Detection Systems Through the Use of Bayesian Network Analysis
    (2006-05-03) Williams, Lloyd Carter; Robert StAmant, Committee Chair
    The purpose of this research has been to increase the effectiveness of Intrusion Detection Systems in the enforcement of computer security. Current preventative security measures are clearly inadequate as evidenced by constant examples of compromised computer security seen in the news. Intrusion Detection Systems have been created to respond to the inadequacies of existing preventative security methods. This research presents the two main approaches to Intrusion Detection Systems and the reasons that they too fail to produce adequate security. Promising new methods are attempting to increase the effectiveness of Intrusion Detection Systems with one of the most interesting approaches being that taken by the TIAA system. The TIAA system uses a method based on employing prerequisites and consequences of security attacks to glean cohesive collections of attack data from large data sets. The reasons why the TIAA approach ultimately fails are discussed, and the possibility of using the TIAA system as a preprocessor for recognizing novel attacks is then presented along with the types of data this approach will produce. In the course of this research the VisualBayes software package was created to make use of the data generated by the TIAA system. VisualBayes is a complete graphical system for the creation, manipulation, and evaluation of Bayesian networks. The VisualBayes also uses the Bayesian networks to create a visualization of observations and the probabilities that result from them. This is a new feature that has not been seen in other Bayesian systems up to this point.
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    Dynamic Ontology Driven Learning and Control of Robotic Tool Using Behavior
    (2009-12-07) Williams, Lloyd Carter; Dr. Robert St. Amant , Committee Chair; Dr. Ronald Endicott, Committee Member; Dr. Thomas Honeycutt, Committee Member; Dr. R. Michael Young, Committee Member
    One of the most interesting and rich fields of recent artificial intelligence (AI) research has come from examining embodied agents, the creation of which, poses interesting challenges and opportunities. Many traditional AI approaches which have previously proven successful quickly fail in the face of the unique challenges facing embodied agents. There is extensive multidisciplinary research into solving these problems, employing ideas and theory from not just computer science, but cognitive science, psychology, philosophy, neuroscience, as well as a range of other fields. Although the nature of embodied intelligence has risen to prominence in AI research relatively recently, animal behaviorists have been examining it for decades. One of the most explored areas of research into the nature of natural embodied intelligent agents (animals) involves their use of tools. We believe that the creation of artificial tool using behaviors yields insights into the nature of intelligence. The proposed research will survey animal tool using behaviors and argue that some form of imitation may serve as an integral part of most animal tool using behavior. This claim, for the significance of imitation in tool use, will be supported with results from ethology, psychology and neuroscience. We will present a system based on multidisciplinary research that employs action ontologies to enable robotic imitation. We will demonstrate with this research that if mechanisms for imitative behaviors are implemented on a robotic platform, these imitative mechanisms may then be employed to enable tool using behaviors. While the achievement of tool using behaviors through this type of imitative mechanism is a novel and significant technical achievement in and of itself, it’s success also provides insight into how tool using behaviors may have first arisen in animals.