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Full-Text Articles in Artificial Intelligence and Robotics
Holistic Network Defense: Fusing Host And Network Features For Attack Classification, Jenny W. Ji
Holistic Network Defense: Fusing Host And Network Features For Attack Classification, Jenny W. Ji
Theses and Dissertations
This work presents a hybrid network-host monitoring strategy, which fuses data from both the network and the host to recognize malware infections. This work focuses on three categories: Normal, Scanning, and Infected. The network-host sensor fusion is accomplished by extracting 248 features from network traffic using the Fullstats Network Feature generator and from the host using text mining, looking at the frequency of the 500 most common strings and analyzing them as word vectors. Improvements to detection performance are made by synergistically fusing network features obtained from IP packet flows and host features, obtained from text mining port, processor, logon …
Kernelized Locality-Sensitive Hashing For Fast Image Landmark Association, Mark A. Weems
Kernelized Locality-Sensitive Hashing For Fast Image Landmark Association, Mark A. Weems
Theses and Dissertations
As the concept of war has evolved, navigation in urban environments where GPS may be degraded is increasingly becoming more important. Two existing solutions are vision-aided navigation and vision-based Simultaneous Localization and Mapping (SLAM). The problem, however, is that vision-based navigation techniques can require excessive amounts of memory and increased computational complexity resulting in a decrease in speed. This research focuses on techniques to improve such issues by speeding up and optimizing the data association process in vision-based SLAM. Specifically, this work studies the current methods that algorithms use to associate a current robot pose to that of one previously …
Developing An Effective And Efficient Real Time Strategy Agent For Use As A Computer Generated Force, Kurt Weissgerber
Developing An Effective And Efficient Real Time Strategy Agent For Use As A Computer Generated Force, Kurt Weissgerber
Theses and Dissertations
Computer Generated Forces (CGF) are used to represent units or individuals in military training and constructive simulation. The use of CGF significantly reduces the time and money required for effective training. For CGF to be effective, they must behave as a human would in the same environment. Real Time Strategy (RTS) games place players in control of a large force whose goal is to defeat the opponent. The military setting of RTS games makes them an excellent platform for the development and testing of CGF. While there has been significant research in RTS agent development, most of the developed agents …
Performance Evaluation Of Ad Hoc Routing In A Swarm Of Autonomous Aerial Vehicles, Matthew T. Hyland
Performance Evaluation Of Ad Hoc Routing In A Swarm Of Autonomous Aerial Vehicles, Matthew T. Hyland
Theses and Dissertations
This thesis investigates the performance of three mobile ad hoc routing protocols in the context of a swarm of autonomous unmanned aerial vehicles (UAVs). It is proposed that a wireless network of nodes having an average of 5.1774 log n neighbors, where n is the total number of nodes in the network, has a high probability of having no partitions. By decreasing transmission range while ensuring network connectivity, and implementing multi-hop routing between nodes, spatial multiplexing is exploited whereby multiple pairs of nodes simultaneously transmit on the same channel. The proposal is evaluated using the Greedy Perimeter Stateless Routing (GPSR), …
Using Discovery-Based Learning To Prove The Behavior Of An Autonomous Agent, David N. Mezera
Using Discovery-Based Learning To Prove The Behavior Of An Autonomous Agent, David N. Mezera
Theses and Dissertations
Computer-generated autonomous agents in simulation often behave predictably and unrealistically. These characteristics make them easy to spot and exploit by human participants in the simulation, when we would prefer the behavior of the agent to be indistinguishable from human behavior. An improvement in behavior might be possible by enlarging the library of responses, giving the agent a richer assortment of tactics to employ during a combat scenario. Machine learning offers an exciting alternative to constructing additional responses by hand by instead allowing the system to improve its own performance with experience. This thesis presents NOSTRUM, a discovery-based learning DBL system …