Aim and tasks of the work are to create principles of the incident tolerant computer system security evaluation, to examine the survivability of the modelled computer system examining its dependence on the security mechanism strength using the composed model. The tasks for achieving this aim are:  to analyse the computer system security standards and security models;  to compose the computer system attack classification which incorporates all the main features of the attack;  to model typical threats to the computer system using graph theory;  to perform the experimental study on the computer system security incidents;  to analyse security mechanisms evaluating the modelling abilities;  to compose a model of the computer system survivability;  to examine the modelled computer system survivability dependence on the security mechanism strength.

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Cloud infrastructure services are enabling organizations and enterprises to outsource a wide range of computing, storage, and networking needs to external service providers. These offerings make extensive use of underlying network virtualization, i.e., virtual network (VN) embedding, techniques to provision and interconnect customized storage/computing resource pools across large network substrates. However, as cloud-based services continue to gain traction, there is a growing need to address a range of resiliency concerns, particularly with regards to large-scale outages. These conditions can be triggered by events such as natural disasters, malicious man-made attacks, and even cascading power failures. Overall, a wide range of studies have looked at network virtualization survivability, with most efforts focusing on pre-fault protection strategies to set aside backup datacenter and network bandwidth resources. These contributions include single node/link failure schemes as well as recent studies on correlated multi-failure \disaster" recovery schemes. However, pre-fault provisioning is very resource-intensive and imposes high costs for clients. Moreover this approach cannot guarantee recovery under generalized multi-failure conditions. Although post-fault restoration (remapping) schemes have also been studied, the effectiveness of these methods is constrained by the scale of infrastructure damage. As a result there is a pressing need to investigate longer-term post-fault infrastructure repair strategies to minimize VN service disruption. However this is a largely unexplored area and requires specialized consideration as damaged infrastructures will likely be repaired in a time-staged, incremental manner, i.e., progressive recovery. Furthermore, more specialized multicast VN (MVN) services are also being used to support a range of content distribution and real-time streaming needs over cloud-based infrastructures. In general, these one-to-many services impose more challenging requirements in terms of geographic coverage, delay, delay variation, and reliability. Now some recent studies have looked at MVN embedding and survivability design. In particular, the latter contributions cover both pre-fault protection and post-fault restoration methods, and also include some multi-failure recovery techniques. Nevertheless, there are no known efforts that incorporate risk vulnerabilities into the MVN embedding process. Indeed, there is a strong need to develop such methods in order to reduce the impact of large-scale outages, and this remains an open topic area. In light of the above, this dissertation develops some novel solutions to further improve the resiliency of the network virtualization services in the presence of large outages. Foremost, new multi-stage (progressive) infrastructure repair strategies are proposed to improve the post-fault recovery of VN services. These contributions include advanced simulated annealing metaheuristics as well as more scalable polynomial-time heuristic algorithms. Furthermore, enhanced \risk-aware" mapping solutions are also developed to achieve more reliable multicast (MVN) embedding, providing a further basis to develop more specialized repair strategies in the future. The performance of these various solutions is also evaluated extensively using custom-developed simulation models.

In this study a modern hydrocode, blastFoam, that was designed for multi-phase compressible flow problems with applications suited for high-explosive detonation was investigated for underwater explosion (UNDEX) events. The problem of over-prediction for long-term UNDEX bubble behavior in modern hydrocodes that is known to be due to neglected secondary energy-loss mechanisms is evaluated. A single secondary energy-loss mechanism is established as the most significant loss mechanism that is being disregarded in current hydrocodes. The leading secondary energy-loss mechanism is formulated into a computational model that modifies the Jones-Wilkins-Lee (JWL) equation of state (EOS). Explanation and guidance for implementing the model in an Finite Volume Method (FVM) Eulerian-based hydrocode is provided. Through this research this thesis aims to improve long-term UNDEX bubble behavior prediction. Which is apart of a larger effort to improve numerical and computational predictions of UNDEX-induced structural ship response. / M.S. / Predicting the bubble dynamics of an underwater explosion (UNDEX) event is of great importance for the survivability of America’s warships. Shock waves from high-energy explosives are destructive to anything and everything nearby. Therefore, the design and development of military machinery rely on the accurate predictions of computational simulations. Computational solvers must be able to simulate the initial propagating shock waves from an underwater explosion, as well as the smaller following shock waves from the oscillating UNDEX bubble. Current incompressible solvers neglect the important compressible effects needed to predict the behavior for the UNDEX bubble oscillation cycle. If America’s Navy cannot predict the long-term damaging effects that a warship may encounter from an UNDEX bubble, then America’s warships and crew could not survive at battle. This study considers the assumptions used to simplify current UNDEX computational solvers in order to investigate and organize a compressible long-term simulation model. This model improves the multi-pulse bubble dynamic predictions for an UNDEX event, and will in return help design a long-term battle-ready warship for America’s future warfare.

This dissertation describes the development and application of a naval ship distributed system architectural framework, Architecture Flow Optimization (AFO), and Dynamic Architecture Flow Optimization (DAFO) to naval ship Concept and Requirements Exploration (CandRE). The architectural framework decomposes naval ship distributed systems into physical, logical, and operational architectures representing the spatial, functional, and temporal relationships of distributed systems respectively. This decomposition greatly simplifies the Mission, Power, and Energy System (MPES) design process for use in CandRE. AFO and DAFO are a network-based linear programming optimization methods used to design and analyze MPES at a sufficient level of detail to understand system energy flow, define MPES architecture and sizing, model operations, reduce system vulnerability and improve system reliability. AFO incorporates system topologies, energy coefficient component models, preliminary arrangements, and (nominal and damaged) steady state scenarios to minimize the energy flow cost required to satisfy all operational scenario demands and constraints. DAFO applies the same principles as AFO and adds a second commodity, data flow. DAFO also integrates with a warfighting model, operational model, and capabilities model that quantify tasks and capabilities through system measures of performance at specific capability nodes. This enables the simulation of operational situations including MPES configuration and operation during CandRE. This dissertation provides an overview of design tools developed to implement this process and methods, including objective attribute metrics for cost, effectiveness and risk, ship synthesis model, hullform exploration and MPES explorations using design of experiments (DOEs) and response surface models. / Doctor of Philosophy / This dissertation describes the development and application of a warship system architectural framework, Architecture Flow Optimization (AFO), and Dynamic Architecture Flow Optimization (DAFO) to warship Concept and Requirements Exploration (CandRE). The architectural framework decomposes warship systems into physical, logical, and operational architectures representing the spatial, functional, and time-based relationships of systems respectively. This decomposition greatly simplifies the Mission, Power, and Energy System (MPES) design process for use in CandRE. AFO and DAFO are a network-based linear programming optimization methods used to design and analyze MPES at a sufficient level of detail to understand system energy usage, define MPES connections and sizing, model operations, reduce system vulnerability and improve system reliability. AFO incorporates system templates, simple physics and energy-based component models, preliminary arrangements, and simple undamaged/damaged scenarios to minimize the energy flow usage required to satisfy all operational scenario demands and constraints. DAFO applies the same principles and adds a second commodity, data flow representing system operation. DAFO also integrates with a warfighting model, operational model, and capabilities model that quantify tasks and capabilities through system measures of performance. This enables the simulation of operational situations including MPES configuration and operation during CandRE. This dissertation provides an overview of design tools developed to implement this process and methods, including optimization objective attribute metrics for cost, effectiveness and risk.

Flow temperature sensing remains important for many hypersonic aerodynamics and propulsion applications. Flight test applications, in particular, demand robust and accurate sensing, making thermocouple sensors attractive. Even for these extremely well-developed sensors, the prediction of stresses (hoop, radial, and axial) within thermocouple sheaths for custom-configured probes remains a topic of great concern for ensuring adequate lifetime of sensors. In contemporary practice, high-fidelity simulations must be run to prove if a new design will work at all, albeit at significant time and expense. Given the time and money it takes to run high-fidelity simulations, rapid optimization of sensor configurations is often impossible, or at a minimum, impractical. The developments presented in this Thesis address the need for hypersonic flow temperature sensor structural predictions which are compatible with rapid design iteration. The derivation and implementation of a new analytical, low-order model to predict stresses (hoop, radial, and axial) within the sheath of a thermocouple are provided. The analytical model is compared to high-fidelity ANSYS mechanical simulations as well as simplified experimental data. The predictions using the newly developed structural low-order model are in excellent agreement with the numerically simulated results and experimental results with an absolute maximum percent error of approximately 4% and 9.5%, respectively, thus validating the model. A MATLAB GUI composed of the combination of a thermal low-order model outlined in additional references [1] through [6] and the new structural low-order model for thermocouples was developed. This code is capable of solving a highly generalized version of the 1-D pin fin equation, allowing for the solution of the temperature distribution in a sensor taking into account conduction, convection, and radiation heat transfer which is not possible with other existing analytical solutions. This temperature distribution is then used in the analytical structural low-order model. This combination allows for the thermal and structural performance of a thermocouple to be found analytically and compared quickly with other designs. / M.S. / Thermocouples are a device for measuring temperature, consisting of two wires of different metals connected at two different points. This configuration produces a temperature-dependent voltage as a result of the thermoelectric effect. Preexisting curves are used to relate the voltage to temperature. Thermocouples are extensively used in high-temperature high-stress environments such as in rockets, jet engines, or any high-corrosive environment. Accurately predicting the stresses within the sheath of a metal-clad thermocouple in extreme conditions is required for many research areas including hypersonic aerodynamics and various propulsion applications. Even for these extremely well-developed and widely used sensors, the accurate prediction of stresses within the metal sheath remains a topic of great concern for ensuring the sensor’s survivability in these extreme conditions. Current engineering practice is to use high-fidelity numerical simulations (Finite Element Analysis) to predict the stresses within the sheath. Perhaps the biggest drawback to this approach is the time it takes to model, mesh, and set-up these simulations. Comparative studies between different designs using numerical simulations are almost impossible due to the time requirement. This Thesis will present an analytically derived quasi-3D solution to find the stresses within the sheath. These equations were implemented into a low-order model that can handle varying temperature, geometry, and material inputs. This model was validated against both high-fidelity numerical simulations (ANSYS Mechanical) and a simplified experiment. The predictions using this newly developed structural low-order model are in excellent agreement with the numerically simulated results and experimental results.

This thesis describes the application of a distributed system architecture framework and Architecture Flow Optimization (AFO) to naval ship Concept & Requirements Exploration (C&RE). It describes refinements to both C&RE and AFO, and naval surface combatant concept design case studies. The architectural framework decomposes naval ship distributed systems into the physical, logical, and operational architectures representing the spatial, functional, and temporal relationships of distributed systems respectively. This decomposition greatly simplifies the Mission, Power, and Energy System (MPES) design process for use in C&RE. AFO is a network-based linear programming optimization method used to design and analyze MPES at a sufficient level of detail to understand system energy flow, define MPES architecture and sizing, reduce system vulnerability and improve system reliability. AFO incorporates system topologies, energy coefficient component models, preliminary arrangements, and (nominal and damaged) steady state scenarios to minimize the energy flow cost required to satisfy all operational scenario demands and constraints. This thesis provides an overview of design tools developed to implement this process and methods, including objective attribute metrics for cost, effectiveness and risk, ship synthesis model, hullform exploration and MPES explorations using design of experiments (DOEs) and response surface models. / M.S. / The design of modern warships presents many unique challenges not faced in the design of most commercial ships or past generations of warships. The objectives of warship design (e.g. effectiveness, design risk, and total lifecycle cost) cannot be summarized in a single quantitative metric as commonly done in commercial ship design (e.g. required freight rate: the minimum market price of a commodity to make a commercial ship design with a certain cargo capacity profitable). Furthermore, misison, power, and energy systems (MPES) of modern warships have become increasingly interdependent and complex, especially those of naval surface combatants (non-submarine warships designed to engage in direct combat with other ships). Determining quantitative metrics for these objectives is a difficult task to begin with. Determining accurate values for these metrics in early stage design (when designs have little detailed specifications and some technologies may even be still be in development) is another challenge altogether. This thesis describes simple and robust methods and processes to evaluate a warship’s arrangement and operational characteristics. Survivability characteristics, characteristics related to a warship’s ability to complete missions despite battle damage, are of particular interest in these methods. These methods incorporate physics and energy-based means of assessment rather than using historical parametric models that are insufficient in assessing new and revolutionary warship designs.

For ensuring network survivability in case of single component failures many routing protocols provide a primary and a back up routing path for each origin destination pair. We address the problem of selecting these paths such that in the event of multiple failures, occuring with given probabilities, the total loss in routable demand due to both paths being intersected is small with high probability. We present a chance constraint model and solution approaches based on an explicit integer programming formulation, a robust formulation and a cutting plane approach that yield reasonably good solutions assuming that the failures are caused by at most two elementary events, which may each affect several network components.

For ensuring network survivability in case of single component failures many routing protocols provide a primary and a back up routing path for each origin destination pair. We address the problem of selecting these paths such that in the event of multiple failures, occuring with given probabilities, the total loss in routable demand due to both paths being intersected is small with high probability. We present a chance constraint model and solution approaches based on an explicit integer programming formulation, a robust formulation and a cutting plane approach that yield reasonably good solutions assuming that the failures are caused by at most two elementary events, which may each affect several network components.

Disasters especially from natural phenomena are inevitable. The affected areas recover from the aftermath of a natural disaster with the support from various agents participating in humanitarian operations. There are several domains of the operation, and distributing relief aids is one. For distribution, satisfying the demand for relief aid is important since the condition of the environment is unfavorable to affected people and resources needed for the victim’s life are scarce. However, it becomes problematic when the logistic agents believed to be work properly fail to deliver the emergency goods because of the capacity loss induced from the environment after disasters. This study was proposed to address the problem of logistic agents’ unexpected incapacity which hinders scheduled distribution. The decrease in a logistic agent’s supply capability delays<br>achieving the goal of supplying required relief goods to the affected people which further endangers them. Regarding the stated problem, this study explored the importance of<br>setting the profile of logistic agents that can survive for certain duration of times. Therefore, this research defines the “survivability” and the profile of logistic agents for surviving the last mile distribution through agent based modeling and simulation. Through simulations, this study uncovered that the logistic exercise could gain survivability with the certain number and organization of logistic agents. Proper formation of organization establish the logistics’ survivability, but excessive size can threaten the survivability.