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  Partner: UNT Libraries
 Degree Discipline: Computer Science
 Collection: UNT Theses and Dissertations
Mobile agent security through multi-agent cryptographic protocols.

Mobile agent security through multi-agent cryptographic protocols.

Date: May 2004
Creator: Xu, Ke
Description: An increasingly promising and widespread topic of research in distributed computing is the mobile agent paradigm: code travelling and performing computations on remote hosts in an autonomous manner. One of the biggest challenges faced by this new paradigm is security. The issue of protecting sensitive code and data carried by a mobile agent against tampering from a malicious host is particularly hard but important. Based on secure multi-party computation, a recent research direction shows the feasibility of a software-only solution to this problem, which had been deemed impossible by some researchers previously. The best result prior to this dissertation is a single-agent protocol which requires the participation of a trusted third party. Our research employs multi-agent protocols to eliminate the trusted third party, resulting in a protocol with minimum trust assumptions. This dissertation presents one of the first formal definitions of secure mobile agent computation, in which the privacy and integrity of the agent code and data as well as the data provided by the host are all protected. We present secure protocols for mobile agent computation against static, semi-honest or malicious adversaries without relying on any third party or trusting any specific participant in the system. The security of ...
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Modeling Alcohol Consumption Using Blog Data

Modeling Alcohol Consumption Using Blog Data

Date: May 2013
Creator: Koh, Kok Chuan
Description: How do the content and writing style of people who drink alcohol beverages stand out from non-drinkers? How much information can we learn about a person's alcohol consumption behavior by reading text that they have authored? This thesis attempts to extend the methods deployed in authorship attribution and authorship profiling research into the domain of automatically identifying the human action of drinking alcohol beverages. I examine how a psycholinguistics dictionary (the Linguistics Inquiry and Word Count lexicon, developed by James Pennebaker), together with Kenneth Burke's concept of words as symbols of human action, and James Wertsch's concept of mediated action provide a framework for analyzing meaningful data patterns from the content of blogs written by consumers of alcohol beverages. The contributions of this thesis to the research field are twofold. First, I show that it is possible to automatically identify blog posts that have content related to the consumption of alcohol beverages. And second, I provide a framework and tools to model human behavior through text analysis of blog data.
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Modeling and Analysis of Next Generation 9-1-1 Emergency Medical Dispatch Protocols

Modeling and Analysis of Next Generation 9-1-1 Emergency Medical Dispatch Protocols

Date: August 2013
Creator: Gupta, Neeraj Kant
Description: Emergency Medical Dispatch Protocols are guidelines that a 9-1-1 dispatcher uses to evaluate the nature of emergency, resources to send and the nature of help provided to the 9-1-1 caller. The current Dispatch Protocols are based on voice only call. But the Next Generation 9-1-1 (NG9-1-1) architecture will allow multimedia emergency calls. In this thesis I analyze and model the Emergency Medical Dispatch Protocols for NG9-1-1 architecture. I have identified various technical aspects to improve the NG9-1-1 Dispatch Protocols. The devices (smartphone) at the caller end have advanced to a point where they can be used to send and receive video, pictures and text. There are sensors embedded in them that can be used for initial diagnosis of the injured person. There is a need to improve the human computer (smartphone) interface to take advantage of technology so that callers can easily make use of various features available to them. The dispatchers at the 9-1-1 call center can make use of these new protocols to improve the quality and the response time. They will have capability of multiple media streams to interact with the caller and the first responders.The specific contributions in this thesis include developing applications that use smartphone ...
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Modeling Complex Forest Ecology in a Parallel Computing Infrastructure

Modeling Complex Forest Ecology in a Parallel Computing Infrastructure

Date: August 2003
Creator: Mayes, John
Description: Effective stewardship of forest ecosystems make it imperative to measure, monitor, and predict the dynamic changes of forest ecology. Measuring and monitoring provides us a picture of a forest's current state and the necessary data to formulate models for prediction. However, societal and natural events alter the course of a forest's development. A simulation environment that takes into account these events will facilitate forest management. In this thesis, we describe an efficient parallel implementation of a land cover use model, Mosaic, and discuss the development efforts to incorporate spatial interaction and succession dynamics into the model. To evaluate the performance of our implementation, an extensive set of simulation experiments was carried out using a dataset representing the H.J. Andrews Forest in the Oregon Cascades. Results indicate that a significant reduction in the simulation execution time of our parallel model can be achieved as compared to uni-processor simulations.
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Modeling Infectious Disease Spread Using Global Stochastic Field Simulation

Modeling Infectious Disease Spread Using Global Stochastic Field Simulation

Date: August 2006
Creator: Venkatachalam, Sangeeta
Description: Susceptibles-infectives-removals (SIR) and its derivatives are the classic mathematical models for the study of infectious diseases in epidemiology. In order to model and simulate epidemics of an infectious disease, a global stochastic field simulation paradigm (GSFS) is proposed, which incorporates geographic and demographic based interactions. The interaction measure between regions is a function of population density and geographical distance, and has been extended to include demographic and migratory constraints. The progression of diseases using GSFS is analyzed, and similar behavior to the SIR model is exhibited by GSFS, using the geographic information systems (GIS) gravity model for interactions. The limitations of the SIR and similar models of homogeneous population with uniform mixing are addressed by the GSFS model. The GSFS model is oriented to heterogeneous population, and can incorporate interactions based on geography, demography, environment and migration patterns. The progression of diseases can be modeled at higher levels of fidelity using the GSFS model, and facilitates optimal deployment of public health resources for prevention, control and surveillance of infectious diseases.
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Modeling the Impact and Intervention of a Sexually Transmitted Disease: Human Papilloma Virus

Modeling the Impact and Intervention of a Sexually Transmitted Disease: Human Papilloma Virus

Date: May 2006
Creator: Corley, Courtney D.
Description: Many human papilloma virus (HPV) types are sexually transmitted and HPV DNA types 16, 18, 31, and 45 account for more than 75% if all cervical dysplasia. Candidate vaccines are successfully completing US Federal Drug Agency (FDA) phase III testing and several drug companies are in licensing arbitration. Once this vaccine become available it is unlikely that 100% vaccination coverage will be probable; hence, the need for vaccination strategies that will have the greatest reduction on the endemic prevalence of HPV. This thesis introduces two discrete-time models for evaluating the effect of demographic-biased vaccination strategies: one model incorporates temporal demographics (i.e., age) in population compartments; the other non-temporal demographics (i.e., race, ethnicity). Also presented is an intuitive Web-based interface that was developed to allow the user to evaluate the effects on prevalence of a demographic-biased intervention by tailoring the model parameters to specific demographics and geographical region.
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Multi-Agent Architecture for Internet Information Extraction and Visualization

Multi-Agent Architecture for Internet Information Extraction and Visualization

Access: Use of this item is restricted to the UNT Community.
Date: August 2000
Creator: Gollapally, Devender R.
Description: The World Wide Web is one of the largest sources of information; more and more applications are being developed daily to make use of this information. This thesis presents a multi-agent architecture that deals with some of the issues related to Internet data extraction. The primary issue addresses the reliable, efficient and quick extraction of data through the use of HTTP performance monitoring agents. A second issue focuses on how to make use of available data to take decisions and alert the user when there is change in data; this is done with the help of user agents that are equipped with a Defeasible reasoning interpreter. An additional issue is the visualization of extracted data; this is done with the aid of VRML visualization agents. The cited issues are discussed using stock portfolio management as an example application.
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Multi-perspective, Multi-modal Image Registration and Fusion

Multi-perspective, Multi-modal Image Registration and Fusion

Date: August 2012
Creator: Belkhouche, Mohammed Yassine
Description: Multi-modal image fusion is an active research area with many civilian and military applications. Fusion is defined as strategic combination of information collected by various sensors from different locations or different types in order to obtain a better understanding of an observed scene or situation. Fusion of multi-modal images cannot be completed unless these two modalities are spatially aligned. In this research, I consider two important problems. Multi-modal, multi-perspective image registration and decision level fusion of multi-modal images. In particular, LiDAR and visual imagery. Multi-modal image registration is a difficult task due to the different semantic interpretation of features extracted from each modality. This problem is decoupled into three sub-problems. The first step is identification and extraction of common features. The second step is the determination of corresponding points. The third step consists of determining the registration transformation parameters. Traditional registration methods use low level features such as lines and corners. Using these features require an extensive optimization search in order to determine the corresponding points. Many methods use global positioning systems (GPS), and a calibrated camera in order to obtain an initial estimate of the camera parameters. The advantages of our work over the previous works are the following. ...
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A Multi-Time Scale Learning Mechanism for Neuromimic Processing

A Multi-Time Scale Learning Mechanism for Neuromimic Processing

Date: August 1994
Creator: Mobus, George E. (George Edward)
Description: Learning and representing and reasoning about temporal relations, particularly causal relations, is a deep problem in artificial intelligence (AI). Learning such representations in the real world is complicated by the fact that phenomena are subject to multiple time scale influences and may operate with a strange attractor dynamic. This dissertation proposes a new computational learning mechanism, the adaptrode, which, used in a neuromimic processing architecture may help to solve some of these problems. The adaptrode is shown to emulate the dynamics of real biological synapses and represents a significant departure from the classical weighted input scheme of conventional artificial neural networks. Indeed the adaptrode is shown, by analysis of the deep structure of real synapses, to have a strong structural correspondence with the latter in terms of multi-time scale biophysical processes. Simulations of an adaptrode-based neuron and a small network of neurons are shown to have the same learning capabilities as invertebrate animals in classical conditioning. Classical conditioning is considered a fundamental learning task in animals. Furthermore, it is subject to temporal ordering constraints that fulfill the criteria of causal relations in natural systems. It may offer clues to the learning of causal relations and mechanisms for causal reasoning. The ...
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A Multi-Variate Analysis of SMTP Paths and Relays to Restrict Spam and Phishing Attacks in Emails

A Multi-Variate Analysis of SMTP Paths and Relays to Restrict Spam and Phishing Attacks in Emails

Access: Use of this item is restricted to the UNT Community.
Date: December 2006
Creator: Palla, Srikanth
Description: The classifier discussed in this thesis considers the path traversed by an email (instead of its content) and reputation of the relays, features inaccessible to spammers. Groups of spammers and individual behaviors of a spammer in a given domain were analyzed to yield association patterns, which were then used to identify similar spammers. Unsolicited and phishing emails were successfully isolated from legitimate emails, using analysis results. Spammers and phishers are also categorized into serial spammers/phishers, recent spammers/phishers, prospective spammers/phishers, and suspects. Legitimate emails and trusted domains are classified into socially close (family members, friends), socially distinct (strangers etc), and opt-outs (resolved false positives and false negatives). Overall this classifier resulted in far less false positives when compared to current filters like SpamAssassin, achieving a 98.65% precision, which is well comparable to the precisions achieved by SPF, DNSRBL blacklists.
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