Despite the recent advances in systems and network security, attacks on large enterprise networks consistently impose serious challenges to maintaining data privacy and software service integrity. We identify two main problems that contribute to increasing the security risk in a networked environment: (i) vulnerable servers, workstations, and mobile devices that suffer from vulnerabilities, which allow the execution of various cyber attacks, and, (ii) poor security and system configurations that create loopholes used by attackers to bypass implemented security defenses. Complex attacks on large networks are only possible with the existence of vulnerable intermediate machines, routers, or mobile devices (that we refer to as network components) in the network. Vulnerabilities in highly connected servers and workstations, that compromise the heart of today's networks, are inevitable. Also, modern mobile devices with known vulnerabilities cause an increasing risk on large networks. Thus, weak security mechanisms in vulnerable  network components open the possibilities for effective network attacks On the other hand, lack of systematic methods for an effective static analysis of an overall complex network results in inconsistent and vulnerable configurations at individual network components as well as at the network level. For example, inconsistency and faults in designing firewall rules at a host may result in enabling more attack vector. Further, the dynamic nature of networks with changing network configurations, machine availability and connectivity, make the security analysis a challenging task This work presents a hybrid approach to security by providing two solutions for analyzing the overall security of large organizational networks, and a runtime  framework for protecting individual network components against misuse of system resources by cyber attackers. We  observe that to secure an overall computing environment, a static analysis of a network is not sufficient. Thus, we couple our analysis with a framework to secure individual network components including high performance machines as well as mobile devices that repeatedly enter and leave networks. We also realize the need for advancing the theoretical foundations for analyzing the security of large networks. To analyze the security of large enterprise network, we present the first scientific attempt to compute an optimized distribution of defensive resources with the objective of minimizing the chances of successful attacks. To achieve this minimization, we develop a rigorous probabilistic model that quantitatively measures the chances of a successful attack on any network component. Our model provides a solid theoretical foundation that enables efficient computation of unknown success probabilities on every stage of a network attack. We design an algorithm that uses the computed attack probabilities for optimizing security configurations of a network. Our optimization algorithm  uses state of the art sequential linear programming to approximate the solution to a complex single objective nonlinear minimization problem that formalizes various attack steps and candidate defenses at the granularity of attack stages. To protect individual network components, we develop a new approach under our novel idea of em process authentication. We argue that to provide high assurance security, enforcing authorization is necessary but not sufficient. In fact, existing authorization systems lack a strong and reliable process authentication model for preventing the execution of malicious processes (i.e., processes that intentionally contain malicious goals that violate integrity and confidentiality of legitimate processes and data). Authentication is specially critical when malicious processes may use various system vulnerabilities to install on the system and stealthily execute without the user's consent. We design and implement the Application Authentication (A2) framework that is capable of monitoring application executions and ensuring proper authentication of application processes. A2 has the advantage of strong security guarantees, efficient runtime execution, and compatibility with legacy applications. This authentication framework reduces the risk of infection by powerful malicious applications that may disrupt proper execution of legitimate applications, steal users' private data, and spread across the entire organizational network. Our process authentication model is extended and applied to the Android platform. As Android imposes its unique challenges (e.g., virtualized application execution model), our design and implementation of process authentication is extended to address these challenges. Per our results, process authentication in Android can protect the system against various critical vulnerabilities such as privilege escalation attacks and drive by downloads. To demonstrate process authentication in Android, we implement DroidBarrier. As a runtime system, DroidBarrier includes an authentication component and a lightweight permission system to protect legitimate applications and secret authentication information in the file system. Our implementation of DroidBarrier is compatible with the Android runtime (with no need for modifications) and shows efficient performance with negligible penalties in I/O operations and process creations. / Ph. D.

Long-term care facility network in Ontario, and in Canada as a whole, encounters critical issues regarding balancing demand with capacity. Even worse, it is faced with rising demand in the coming years. Moreover, there is an urgent need to provide long-term care for patients in their own language (particularly French). This study proposes a dynamic Mixed-Integer Linear Programming model based on the current standing of the long-term care system in Ontario, which simultaneously optimizes the time and location of constructing new long-term care facilities, adjusting the capacity (namely, human resources and beds) of each facility dynamically, and the assignment of patients to the facilities based on their demand region, gender, language, and age group over a finite time horizon. We apply the diversity-support constraints, based on patients’ gender and language, to save patients from loneliness and to comply with the Canadian values of providing care. Finally, we validate the model by performing a case study in Hamilton, Ontario. An extensive set of numerical analyses are explored to provide deeper insights into the whole issue. One set of such analysis is an extensive simulation study to examine the effect of distributional uncertainty in some of the input parameters on the optimal results, hence providing a much more realistic understanding of the optimization model. / Thesis / Master of Science (MSc)

Farmers' decisions to adopt Integrated Pest Management (IPM) technologies depend on the profitability of IPM systems relative to the traditional production methods. Government policies may affect the profitability of the IPM technologies. A linear programming model was developed and used to evaluate the economic incentives for adoption of Integrated Pest Mangement (IPM) practices by Jamaican farmers in Ebony Park, Clarendon. Further analysis was completed to determine the affect of policy changes on the profitability of the IPM systems. The objective function of the model was to maximize net returns above variable costs for the farm and included: ten cropping systems, resource constraints, relative prices, and government policies facing the farm. Resource constraints included risk constraints limiting the maximum acreage planted for each crop. Potential crops grown by the farm included: IPM and conventional hot pepper, IPM and conventional sweet potato, IPM and conventional callaloo, corn, pumpkin, cassava, and sugar cane. The trade and domestic policies incorporated into the model were: preclearance (farm level inspections of exportable harvest), elimination of the concessionary water rates to farmers, lowering the duty concession rate to farmers, lowering the Common External Tariff, appreciation of the real exchange rate, elimination of the credit subsidy and a fall in the real interest rate. The results of the model showed four major conclusions. First, the IPM systems for hot pepper, sweet potato and callaloo were more profitable than the conventional systems. Second, within the framework of risk constraints and preclearance, the IPM systems continued to be more profitable than the conventional practices. Third, the elimination of either the water or credit subsidies currently available to the farmers did not greatly affect the profitability of the IPM systems compared with the profitability of conventional production. Fourth, with a lower real interest rate, the elimination of the duty concession, a lowering of the Common External Tariff (CET) or an appreciation of the real exchange rate, the IPM systems were more profitable than the conventional technologies. Four implications arose from the conclusions. First, extension efforts towards farmers should emphasize the increase in profits from the IPM technologies. Second, policy steps designed to liberalize the domestic economy will not require offsetting policies supporting the adoption of IPM by farmers in Clarendon. Further research is needed on the effects of water availability on IPM adoption and the potential barriers to IPM adoption by female-headed households. Finally, further research is on the economic returns of incorporating preclearance education with IPM. / Master of Science

No description available.

O Método dos Elementos Finitos quando aplicado à análise de estruturas, em sua forma usual, conduz a sistemas de equações que, no caso não-linear, exigem algoritmos iterativos que realizam, em essência, uma linearização a cada passo de carga. Por outro lado, o Método da Energia formula o problema de análise estrutural na forma de uma minimização, podendo apresentar restrições sobre a função deslocamento, por exemplo. Nesse caso, os algoritmos de programação matemática proporcionam a maneira mais consistente para a obtenção da solução. O presente trabalho de mestrado trata, essencialmente, da aplicação das técnicas de otimização como ferramenta para a análise do comportamento não-linear de estruturas, que pode ser decorrente de condições de vinculação. Os problemas estruturais são formulados via Método da Energia, que resulta na minimização de funções quadráticas sujeitas a um conjunto de restrições. São discutidos os métodos do tipo Gradiente, Newton e Quase-Newton, com a descrição dos seus algoritmos básicos e apresentação da regra de busca unidimensional adotada (Regra de Armijo ou Exata). Devido ao fato do Método de Newton ter apresentado uma melhor convergência em relação aos demais algoritmos estudados, optou-se por combiná-lo com uma estratégia de conjuntos ativos para o caso de minimização com variáveis canalizadas. / The finite element method when applied to structural analysis, in its usual form, it drives the equations systems that, in the nonlinear case, they demand algorithms repetitive that accomplish, in essence, a linear programming to each load step. However, the Energy Method formulates the problem of structural analysis in the form of the minimizing, could present restrictions on the displacement function, for example. In that case, the algorithms of mathematical programming provide the most consistent way for obtaining of the solution. The present work negotiates, essentially, of the application in mathematical programming as a form to analyze the nonlinear structures behavior, that can be current of boundary conditions. The structural problems are formulated through Energy Method, that results in the mathematical programming of quadratic functions subject to a group of restrictions. The methods of the type Gradient are discussed, of Newton and Quasi-Newton, with the description of its basic algorithms and presentation of the rule of search adopted unidimensional (Rule of Armijo or Exact). Due to the fact of Newton\'s Method to have presented a better convergence in relation to the other studied algorithms, it was opted for combining it with a \"strategy of the active groups\" for the case of mathematical programming with restricted variables.

Šio darbo pagrindinis tikslas yra suprojektuoti ir sukurti internetinę matematinio programavimo ir modeliavimo sistemą. Šiam tikslui pasiekti buvo nagrinėjama matematinio programavimo samprata. Atlikta panašių matematinių programavimo sistemų bei matematinių funkcijų bibliotekų, skirtų įvairioms programavimo kalboms, analizė. Identifikuojamos ir nagrinėjamos problemos, kurios iškilo kuriant internetinę matematinio programavimo ir modeliavimo sistemą. Taip pat šiai sistemai parašytos testinės programos su C++, Java, Fortran programavimo kalbomis bei Netlib Repository LAPACK ir QT bibliotekomis. Sukurta sistema palyginta su Mathematica ir Scilab matematinio programavimo sistemomis. / The aim of this work is to design and develop web-based mathematical programming and simulation system. For this purpose were analyzed the concept of mathematical programming and performed analysis of similar mathematical programming systems and libraries of mathematical functions for various programming languages. Identified and analyzed the problems that arose in the development of an online mathematical programming and simulation system. Also, written test programs for created system in C++, Java, Fortran programming languages and Netlib Repository LAPACK, QT libraries. The developed system was compared with Mathematica and Scilab mathematical programming systems.

O Método dos Elementos Finitos quando aplicado à análise de estruturas, em sua forma usual, conduz a sistemas de equações que, no caso não-linear, exigem algoritmos iterativos que realizam, em essência, uma linearização a cada passo de carga. Por outro lado, o Método da Energia formula o problema de análise estrutural na forma de uma minimização, podendo apresentar restrições sobre a função deslocamento, por exemplo. Nesse caso, os algoritmos de programação matemática proporcionam a maneira mais consistente para a obtenção da solução. O presente trabalho de mestrado trata, essencialmente, da aplicação das técnicas de otimização como ferramenta para a análise do comportamento não-linear de estruturas, que pode ser decorrente de condições de vinculação. Os problemas estruturais são formulados via Método da Energia, que resulta na minimização de funções quadráticas sujeitas a um conjunto de restrições. São discutidos os métodos do tipo Gradiente, Newton e Quase-Newton, com a descrição dos seus algoritmos básicos e apresentação da regra de busca unidimensional adotada (Regra de Armijo ou Exata). Devido ao fato do Método de Newton ter apresentado uma melhor convergência em relação aos demais algoritmos estudados, optou-se por combiná-lo com uma estratégia de conjuntos ativos para o caso de minimização com variáveis canalizadas. / The finite element method when applied to structural analysis, in its usual form, it drives the equations systems that, in the nonlinear case, they demand algorithms repetitive that accomplish, in essence, a linear programming to each load step. However, the Energy Method formulates the problem of structural analysis in the form of the minimizing, could present restrictions on the displacement function, for example. In that case, the algorithms of mathematical programming provide the most consistent way for obtaining of the solution. The present work negotiates, essentially, of the application in mathematical programming as a form to analyze the nonlinear structures behavior, that can be current of boundary conditions. The structural problems are formulated through Energy Method, that results in the mathematical programming of quadratic functions subject to a group of restrictions. The methods of the type Gradient are discussed, of Newton and Quasi-Newton, with the description of its basic algorithms and presentation of the rule of search adopted unidimensional (Rule of Armijo or Exact). Due to the fact of Newton\'s Method to have presented a better convergence in relation to the other studied algorithms, it was opted for combining it with a \"strategy of the active groups\" for the case of mathematical programming with restricted variables.

This thesis consists of two parts. The first part (Chapters 2-4) considers multilevel Monte Carlo for option pricing in finite activity jump-diffusion models. We use a jump-adapted Milstein discretisation for constant rate cases and with the thinning method for bounded state-dependent rate cases. Multilevel Monte Carlo estimators are constructed for Asian, lookback, barrier and digital options. The computational efficiency is numerically demonstrated and analytically justified. The second part (Chapter 5) deals with option pricing problems in exponential Lévy models where the increments of the underlying process can be directly simulated. We discuss several examples: Variance Gamma, Normal Inverse Gaussian and alpha-stable processes and present numerical experiments of multilevel Monte Carlo for Asian, lookback, barrier options, where the running maximum of the Lévy process involved in lookback and barrier payoffs is approximated using discretely monitored maximum. To analytically verify the computational complexity of multilevel method, we also prove some upper bounds on L^p convergence rate of discretely monitored error for a broad class of Lévy processes.

The objective of this thesis is to examine the impacts of changes in Canada’s AgriStability program on crop allocation, particularly the change in the payment trigger associated with the shift from Growing Forward (GF) to Growing Forward 2 (GF2). To examine whether this change could affect production decisions, and thereby potentially violate the WTO’s ‘green box’ criteria, farm management models are constructed for representative farms in six different Alberta regions. To incorporate risk and uncertainty into the farm model, I assume that, instead of maximizing overall gross margin, a farmer varies her crop activities to maximize expected utility subject to technological and market constraints. The models are calibrated using positive mathematical programming (PMP), which then facilitates their use for policy analysis; however, PMP is not straightforward in the case of expected utility maximization because a risk parameter also needs to be calibrated. Possible ways to address this issue are examined. Results indicate that the initial introduction of the AgriStability program tilted farmers’ planting decisions towards crops with higher returns and greater risk, but that a change in the AgriStability payout trigger (going from GF to GF2) would not further alter land-use decisions. However, the latter shift does reduce indemnities and farmers’ expected profits. Meanwhile, increases in farmers’ aversion to risk will lead to changes in crop allocations. / Graduate / 0503 / 0508 / sheriliu@uvic.ca

This research examines certain modifications of the mathematical programming models to improve their classificatory performance. These modifications involve the inclusion of second-order terms and secondary goals in mathematical programming models. A Monte Carlo simulation study is conducted to investigate the performance of two standard parametric models and various mathematical programming models, including the MSD (minimize sum of deviations) model, the MIP (mixed integer programming) model and the hybrid linear programming model.