UNT Theses and Dissertations - 5 Matching Results
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- Direct Online/Offline Digital Signature Schemes.
- Online/offline signature schemes are useful in many situations, and two such scenarios are considered in this dissertation: bursty server authentication and embedded device authentication. In this dissertation, new techniques for online/offline signing are introduced, those are applied in a variety of ways for creating online/offline signature schemes, and five different online/offline signature schemes that are proved secure under a variety of models and assumptions are proposed. Two of the proposed five schemes have the best offline or best online performance of any currently known technique, and are particularly well-suited for the scenarios that are considered in this dissertation. To determine if the proposed schemes provide the expected practical improvements, a series of experiments were conducted comparing the proposed schemes with each other and with other state-of-the-art schemes in this area, both on a desktop class computer, and under AVR Studio, a simulation platform for an 8-bit processor that is popular for embedded systems. Under AVR Studio, the proposed SGE scheme using a typical key size for the embedded device authentication scenario, can complete the offline phase in about 24 seconds and then produce a signature (the online phase) in 15 milliseconds, which is the best offline performance of any known signature scheme that has been proven secure in the standard model. In the tests on a desktop class computer, the proposed SGS scheme, which has the best online performance and is designed for the bursty server authentication scenario, generated 469,109 signatures per second, and the Schnorr scheme (the next best scheme in terms of online performance) generated only 223,548 signatures. The experimental results demonstrate that the SGE and SGS schemes are the most efficient techniques for embedded device authentication and bursty server authentication, respectively.
- Graph-based Centrality Algorithms for Unsupervised Word Sense Disambiguation
- This thesis introduces an innovative methodology of combining some traditional dictionary based approaches to word sense disambiguation (semantic similarity measures and overlap of word glosses, both based on WordNet) with some graph-based centrality methods, namely the degree of the vertices, Pagerank, closeness, and betweenness. The approach is completely unsupervised, and is based on creating graphs for the words to be disambiguated. We experiment with several possible combinations of the semantic similarity measures as the first stage in our experiments. The next stage attempts to score individual vertices in the graphs previously created based on several graph connectivity measures. During the final stage, several voting schemes are applied on the results obtained from the different centrality algorithms. The most important contributions of this work are not only that it is a novel approach and it works well, but also that it has great potential in overcoming the new-knowledge-acquisition bottleneck which has apparently brought research in supervised WSD as an explicit application to a plateau. The type of research reported in this thesis, which does not require manually annotated data, holds promise of a lot of new and interesting things, and our work is one of the first steps, despite being a small one, in this direction. The complete system is built and tested on standard benchmarks, and is comparable with work done on graph-based word sense disambiguation as well as lexical chains. The evaluation indicates that the right combination of the above mentioned metrics can be used to develop an unsupervised disambiguation engine as powerful as the state-of-the-art in WSD.
- Exploring Trusted Platform Module Capabilities: A Theoretical and Experimental Study
- Trusted platform modules (TPMs) are hardware modules that are bound to a computer's motherboard, that are being included in many desktops and laptops. Augmenting computers with these hardware modules adds powerful functionality in distributed settings, allowing us to reason about the security of these systems in new ways. In this dissertation, I study the functionality of TPMs from a theoretical as well as an experimental perspective. On the theoretical front, I leverage various features of TPMs to construct applications like random oracles that are impossible to implement in a standard model of computation. Apart from random oracles, I construct a new cryptographic primitive which is basically a non-interactive form of the standard cryptographic primitive of oblivious transfer. I apply this new primitive to secure mobile agent computations, where interaction between various entities is typically required to ensure security. I prove these constructions are secure using standard cryptographic techniques and assumptions. To test the practicability of these constructions and their applications, I performed an experimental study, both on an actual TPM and a software TPM simulator which has been enhanced to make it reflect timings from a real TPM. This allowed me to benchmark the performance of the applications and test the feasibility of the proposed extensions to standard TPMs. My tests also show that these constructions are practical.
- General Purpose Programming on Modern Graphics Hardware
- I start with a brief introduction to the graphics processing unit (GPU) as well as general-purpose computation on modern graphics hardware (GPGPU). Next, I explore the motivations for GPGPU programming, and the capabilities of modern GPUs (including advantages and disadvantages). Also, I give the background required for further exploring GPU programming, including the terminology used and the resources available. Finally, I include a comprehensive survey of previous and current GPGPU work, and end with a look at the future of GPU programming.
- Keywords in the mist: Automated keyword extraction for very large documents and back of the book indexing.
- This research addresses the problem of automatic keyphrase extraction from large documents and back of the book indexing. The potential benefits of automating this process are far reaching, from improving information retrieval in digital libraries, to saving countless man-hours by helping professional indexers creating back of the book indexes. The dissertation introduces a new methodology to evaluate automated systems, which allows for a detailed, comparative analysis of several techniques for keyphrase extraction. We introduce and evaluate both supervised and unsupervised techniques, designed to balance the resource requirements of an automated system and the best achievable performance. Additionally, a number of novel features are proposed, including a statistical informativeness measure based on chi statistics; an encyclopedic feature that taps into the vast knowledge base of Wikipedia to establish the likelihood of a phrase referring to an informative concept; and a linguistic feature based on sophisticated semantic analysis of the text using current theories of discourse comprehension. The resulting keyphrase extraction system is shown to outperform the current state of the art in supervised keyphrase extraction by a large margin. Moreover, a fully automated back of the book indexing system based on the keyphrase extraction system was shown to lead to back of the book indexes closely resembling those created by human experts.