VictorJuiz/thesis huggingface dataset:
Scalable Security: Cyber Threat Information Sharing in the Internet Age

The federal government has attempted to foster cyber threat information sharing within U.S. critical infrastructure industries for at least 16 years. Such efforts have produced today’s complex constellation of threat analysis centers and sharing organizations in various industries and government agencies, but have brought inconsistent observed improvement in cybersecurity outcomes. Meanwhile, successful but limited sharing relationships have formed separately among private companies and individuals. Objections to information sharing that are raised in the literature and press fall into a limited number of categories, each of which can be refuted relatively easily; the problem is therefore better viewed as a problem of insufficient perceived benefits rather than prohibitive costs.
While history demonstrates that sharing is a powerful tool for addressing collective threats, new analysis is clearly needed to explain why effective cyber sharing seems so difficult to accomplish effectively.
The Computational Policy analytical approach defined herein brings the power of the abstractions used in computer systems design to bear on difficult policy problems, allowing new analytical insights to inform policy choices.
Using this approach and new understanding of the cybersecurity threat landscape, analyses of three archetypal sharing designs—the watch floor, social network, and high-volume data sharing models—are presented and aspects of the current system are questioned.
Cybersecurity programs centered on human analysis are at a disadvantage as networks continue to grow; approaches which harness the power of algorithmic thinking and ever-growing computational resources have better hope of succeeding in the Internet Age.

Keywords: computer security
cybersecurity
cyber security
information sharing
cyber threat information sharing
cybersecurity information sharing
cyber threat sharing
cyber defense sharing
sharing
cyber
computer network defense
Computer Science
CS
Center for International Security and Cooperation
CISAC
Freeman Spogli Institute for International Studies
FSI
Thesis
Advisor: Berson Thomas A.
Hellman Martin E.
Scaling high performance domain-specific language implementation with delite [electronic resource]

The multicore era is now in full swing: single threaded processors with deep complex pipelines have been replaced with an increasing number of simpler processors. The shift to these multicore designs is motivated by the need for energy efficiency in addition to high-performance. There is now mounting evidence that further improvements in energy efficiency and performance will come from heterogeneous hardware. Programming heterogeneous hardware systems is difficult, which limits their utility. Each heterogeneous computing element has its own performance characteristics and pitfalls, and usually comes with its own programming model. This means that applications cannot take advantage of the additional compute power available in these new and emerging systems without a significant parallel programming effort. To simplify the complexity of programming heterogeneous hardware, one viable approach is the use of Domain-Specific Languages (DSLs) to develop algorithms at very high levels of abstraction. A corresponding DSL compiler can then reason about high-level domain knowledge now explicitly encoded in the application and generate efficient implementations of the algorithm for the different heterogeneous computing elements. This shifts most of the burden of parallelization to DSL authors requiring them to combine domain, programming language implementation and parallelization expertise. In this Thesis, we start by discussing the benefits of using such DSLs for parallel heterogeneous programming. We motivate the need for an infrastructure to simplify the effort required to author these high-performance DSLs. We then present the Delite Compiler Framework and Runtime, the result of our effort in designing and implementing such an infrastructure. The framework lifts embedded DSL applications to an intermediate representation (IR), performs generic, parallel, and domain-specific optimizations, and generates an execution graph that targets multiple heterogeneous hardware devices. One key component of this framework is a set of IR nodes, called Delite Ops, which simplify DSL parallelization by providing a set of re-usable and extensible parallel execution patterns. We illustrate the usefulness of Delite by showing examples of DSLs that have been implemented using this framework.

Keywords: Electrical Engineering.
Advisor: Olukotun Oyekunle Ayinde primary advisor. Thesis advisor
Hanrahan P. M. (Patrick Matthew) advisor. Thesis advisor
Kozyrakis Christoforos
Scents and sensibility [electronic resource] : effects of aromas on emotion and decision-making

Aromas offer many advantages over traditional methods of manipulating emotion and influencing behavior, especially in the context of studying the mechanisms of decision-making. Many of the brain areas that are activated when perceiving aromas are also known to be involved in emotion, judgment, and decision-making. Pleasantness in particular has been highlighted as an important dimension of olfaction that influences affect and behavior. However, given the richness and diversity of aroma types and qualities, other qualities of aroma percepts likely influence decision processes as well. The goals of this dissertation were 1) to assess the practicality of using aromas as affective stimuli, 2) to expand work on the dimensionality and structure of olfactory space beyond pleasantness, and 3) to determine mechanisms by which aroma-induced affect can influence decisions. To this end, I first gathered ratings along two dimensions commonly used in affective science, pleasantness and intensity, and found that aromas are organized on the affective circumplex along two main axes corresponding to approach and avoidance tendencies. The reliability of the affective properties of aromas across time and between individuals was found to be high. This result confirmed that aromas are useful as affect induction tools for research, and I report affective ratings for a collection of aromas. In the second study, a dimensionality reduction approach was used to discover dimensions that contribute to perceived aroma pleasantness. Finally, using aromas identified in the first study to elicit affective responses, I tested influences of pleasantness and intensity on decision-making, focusing on decisions involving risk and ambiguity. We found that aroma-induced valence and arousal were able to influence risk-aversion, and the effect of aroma intensity was mediated by activity in the anterior insula. Overall, I demonstrate that aromas are potent affect-inducing stimuli that give rise to multi-dimensional percepts, with correspondingly diverse effects on decision-making.

Keywords: Psychology.
Advisor: Gross James J. (Professor of psychology) primary advisor. Thesis advisor
Knutson Brian primary advisor. Thesis advisor
McClure Samuel M. primary advisor. Thesis advisor
Scheduling, revenue sharing, and user behavior for aggregated demand response [electronic resource]

The modern electric grid can trace its origins back over 100 years. Naturally, many changes and improvements have occurred during this time as new policies and new technologies are incorporated. Although these changes have, in the main, made distributing electrical energy more reliable and economical, the essential role of the grid has not changed significantly - generate sufficient power to match the quantity of power consumed. It has long been acknowledged that the ability for the operator to dynamically adjust both the quantity of power consumed as well as the quantity of power generated would be a major aid in ensuring the electric grid continues to operate economically. Attempting to adjust the consumption of energy in response to challenges faced by the operator is an approach known as demand response and it is the focus of this thesis. Although the concept of demand response is not new, substantial questions remain to be answered. Questions such as how demand response programs could be implemented for residential users, how participants in these programs should be compensated, and how the actions of such residential users can be modeled. This dissertation seeks to answer these questions by establishing and analyzing analytical models. We analyze demand response programs from the point of view of a ``Load Serving Entity, '' or ``aggregator, '' which engages in the energy markets by coordinating and controlling the participants in the program. We describe a novel procedure for direct control of non-preemptive loads by an aggregator. This program is based on a greedy algorithm which schedules the underlying loads in a manner that seeks to reduce the error between the final aggregate load profile and a predefined target profile. Algorithms are presented for two scenarios -- firstly, the case where the loads are known in advance, and secondly where the load demands are stochastic. The aggregator will realize revenue from participating in the energy markets, a portion of which must be returned to the individual users as compensation for being a part of the program. The problem of fairly compensating these users is challenging, and we propose a solution by modeling the scenario in a game theoretic setting and utilizing the concept of the Shapley Value in order to calculate a fair compensation. Finally, we analyze data from an existing demand response program, and model user behavior using a discrete choice modeling framework in order to determine what factors influence the participants response to a program.

Keywords: Electrical Engineering.
Advisor: El Gamal Abbas A. primary advisor. Thesis advisor
Rajagopal Ram advisor. Thesis advisor
Van Roy Benjamin advisor. Thesis advisor
School selection, student assignment, and enrollment in a school district with open enrollment and mandatory choice policies [electronic resource]

This dissertation consists of three papers that explore the open enrollment process in a large urban school district that has a mandatory choice open enrollment policy. The first paper examines patterns of school selection in this district after the introduction of a "strategy-proof" deferred acceptance student assignment algorithm. Because of the presence of this algorithm, families in this district can be expected to reveal their genuine preferences for the school program choices that are offered to them, presenting a unique opportunity to gain insight into how families choose schools. Overall, I find that the ways in which families select schools may limit the positive impact of open enrollment policies on racial integration in district schools. The second paper focuses on families' enrollment responses subsequent to student assignment. I examine the extent to which families attrite from the district or successfully obtain reassignment into another school after being assigned to one school; I also determine the conditions that are associated with greater likelihoods of families taking these actions. I find systematic patterns of enrollment responses that might negatively impact diversity within schools and the district as a whole. The third paper uses the results of the first two papers to construct an agent-based model of the open enrollment process in this district. I find that there is a large amount of stability in enrollment patterns over a simulated ten year period. When I simulate trends in enrollment patterns under policy conditions that the district might consider implementing, I find that engagement efforts that successfully get all families in the district to participate in the school choice process has the largest positive impact on diversity in the district and that replacing information given to families about school achievement levels with school value-added measures causes the largest reduction in the gap between the achievement levels of the schools in which White and Asian students enroll and the schools in which Black and Hispanic students enroll.

Keywords: Education.
Advisor: Reardon Sean F. primary advisor. Thesis advisor
Loeb Susanna advisor. Thesis advisor
Moe Terry M. advisor. Thesis advisor
Sea ice and nitrogen as major controls on phytoplankton production in the Pacific Arctic [electronic resource]

The Pacific Arctic, encompassing the Bering and Chukchi Seas between Alaska and Russia, is a highly productive region characterized by extreme seasonality in light and temperature. These seas host prolific stocks of seabirds and marine mammals, and are the sites of expanding human industrial exploration, including our nation's largest fishery. Seasonally ice-covered, the Bering and Chukchi Seas experience intense phytoplankton blooms as sea ice retreats each spring, fueled by high surface nutrient concentrations replenished over the winter. Of these nutrients, nitrogen (N) by far is in highest demand, owing to high rates of microbial N loss in the shallow, organic matter-rich sediments. The Pacific Arctic is also in the midst of unprecedented change due to anthropogenic warming. Field, modeling, and satellite-based studies have shown that the Chukchi Sea ice pack is thinning and diminishing in area. Compared to a decade ago, sea ice in this region retreats earlier, advances later, and covers far less total area during the summer. In turn, these changes profoundly alter the environment for phytoplankton, the single-celled photosynthetic organisms at the base of the Arctic food web. This thesis explores the roles of sea ice and nitrogen as the key factors that promote and ultimately set limits on phytoplankton production in the dynamic Pacific Arctic ecosystem.

Keywords: Environmental Earth System Science.
Advisor: Arrigo Kevin R. primary advisor. Thesis advisor
Casciotti Karen Lynn
Thomas Leif N. advisor. Thesis advisor
Search for out-of-time decays of stopped particles at the ATLAS detector [electronic resource]

On July 4th 2012, the ATLAS and CMS experiments announced the discovery of a new particle, later declared to be one of possibly many Higgs bosons. The Higgs mechanism has been so successful explaining several striking features of fundamental particle physics it was the topic of the 2013 Nobel Prize in physics. However, this mechanism provides a few problems of it's own. Most importantly, both the mass of the new Higgs boson and the cosmological constant must be extremely fine-tuned to produce a universe remotely similar to the one we observe today. Supersymmetry, a hypothetical extension to the current theory, addresses many problems in theoretical and experimental physics including the fine-tuned Higgs mass. In this work, a variant, called Split-Supersymmetry, is investigated; it avoids some problems in standard Supersymmetry while explicitly leaving the Higgs mass fine-tuned. A experimentally unique feature of Split-Supersymmetry is the production of R-hadrons---composite, massive, long-lived, particles. Indeed such long-lived states are predicted in several scenarios of physics beyond the Standard Model, and this search is sensitive to them as well. This dissertation describes the ATLAS searches using 2010, 2011 and 2012 data for gluino and squark R-hadrons which have come to rest within the ATLAS detector, particularly the calorimeter, and decay at some later time to jets or "ttbar" and a neutralino. Candidate decay events are triggered in the empty bunch crossings in order to remove collision backgrounds. Selections based on jet shape and muon-system activity are applied to discriminate events from backgrounds, the largest of which are cosmic and beam-halo muons. In the absence of a excess, limits are placed on the new particle mass as a function of its lifetime, for various neutralino masses and decay types.

Keywords: Physics.
Advisor: Su Dong
Hewett JoAnne L. advisor. Thesis advisor
Lüth Vera
Seismic modeling, inversion, and imaging in attenuating media [electronic resource]

Accurate seismic exploration demands sophisticated seismic techniques that can be applied to any complex geological setting, for example, attenuative and anisotropic media. This dissertation addresses attenuation problems in seismic exploration: how to model wave propagation in attenuating media, how to invert attenuation property of subsurface reliably, and how to mitigate attenuation effects in seismic images. The key innovations are (1) developing a novel viscoacoustic/elastic constant-Q wave equation that is practically efficient and accurately simulates the constant-Q attenuation behavior, (2) an iterative joint inversion framework for different geophysical datasets (e.g., attenuation data) to reduce the uncertainties of independent inversion results, (3) developing an Q-compensated reverse-time migration approach to compensate for attenuation effects (dispersion and amplitude loss) in seismic images. In the first part, I derive a novel viscoacoustic wave equation based on constant-Q theory. I investigate the accuracy of this wave equation. I show its application in a heterogeneous medium. Testing shows this model to be more computationally efficient than the most efficient single standard linear solid modeling. More importantly, this viscoacoustic equation separates attenuation and dispersion operators that allow us to mitigate both amplitude attenuation and phase dispersion effects in seismic imaging. This equation is the key modeling engine for seismic migration. Due to the data quality of the seismic waveform and the strong nonlinearity of the attenuation problem, I choose a joint inversion algorithm to invert for the attenuation coefficient. I develop an iterative joint inversion approach where one model domain acts as a constraint for inversion of the other, and the roles of the two domains are iteratively switched. This joint inversion stabilizes the inversion and ensures that results are geologically plausible. I apply the method to estimate Vp and the attenuation coefficient in field data examples. In the third part, I present a method to improve the image resolution by mitigating attenuation effects. I discuss the feasibility of time-reverse modeling in attenuating media using numerical experiments for 1D and 2D situations. I develop a Q-compensated reverse-time migration imaging approach (referred as Q-RTM). I illustrate this approach using different synthetic models. Numerical results further verify that this Q-RTM approach can effectively improve the resolution and quality of image, particularly beneath high-attenuation zones. To demonstrate the suitability, I apply the Q-RTM method to field data from the King Mountain site in west Texas. In the future, this method could readily be applied to other field datasets to improve the image resolution in high attenuation areas.

Keywords: Geophysics.
Advisor: Harris Jerry M. primary advisor. Thesis advisor
Biondi Biondo
Clapp Robert G. (Robert Graham) advisor. Thesis advisor
Mukerji Tapan
Seismic resilience of tall buildings - benchmarking performance and quantifying improvements [electronic resource]

Modern tall buildings are generally not considered to be a large contributor to the seismic risk of cities, based on the presumption that they are designed and built with sufficient safeguards to ensure good performance. This is in spite of the fact that current building code provisions have few, if any, provisions to ensure that tall buildings have better performance than other low-rise structures. This implies that a 40-story building is not expected, or designed, to perform any better than a one-story building following a large seismic event, despite the huge differences in the consequences of collapse and/or damage to these type of structures. The performance of a 42-story couple core wall building located in downtown San Francisco, designed using a state-of-the-practice performance-based approach, is evaluated. Two additional structural schemes, damped outriggers and base isolation, and one additional non-structural scheme are investigated. Non-linear response history analysis is conducted on each of the three structural building designs in order to assess the structural performance at five different seismic hazard levels. Subsequently, the expected building repair cost and downtime are estimated for each scheme; there are six schemes in total when considering the additional non-structural design scheme. The baseline building is expected to suffer financial losses exceeding 15% of the total building cost and functional downtime of almost 2 years (84 weeks) following a design level earthquake. The damped outrigger and base isolation schemes are found to reduce financial losses and downtime, with an expected loss of 14% and 10% of the building cost, respectively and an expected functional downtime of 62 weeks and 43 weeks, respectively following a design-level earthquake. The non-structural design alternative, which also includes provisions to reduce building downtime, was found to reduce loss and downtime in all cases. The best performing building is the base-isolated building with enhanced non-structural design, expected to experience losses of 2.4% of the building value and functional downtime of only 6 weeks following a design-level earthquake. A cost-benefit analysis reveals that all schemes are preferable to the baseline building. The payback period for the two structural design alternatives is found to be 4.6 years and 6.6 years for the damped outrigger and the base isolation schemes, respectively, and the payback period for the non-structural design alternatives are 5.3 years, 9.0 years and 8.7 years for the fixed base, damped outrigger and the base isolation schemes, respectively.

Keywords: Civil and Environmental Engineering.
Advisor: Deierlein Gregory G. (Gregory Gerard)
Seismic risk assessment of complex transportation networks [electronic resource]

This dissertation focuses on understanding seismic risk and possible mitigation measures for complex transportation networks. It first introduces frameworks and computationally-feasible strategies for assessing probabilistic risk to these transportation networks, and applies them to a case study of the San Francisco Bay Area. Using these strategies for a set of earthquake events, values of a network-performance measure called "mode-destination accessibility" are then calculated to link physical infrastructure damage with the impact on people's ability to travel to desirable destinations, one measure of post-earthquake human welfare. As a result, at-risk communities are also identified. The results suggest that accessibility varies greatly between communities across the case study region, whereas the differences across income groups are more subtle. Furthermore, increased walkability of a region correlates with lower expected losses in accessibility. Finally, this dissertation contributes an automated framework incorporating seismic risk and network importance into bridge retrofit prioritization. A key finding is that bridges important for the network functionality after an earthquake are not necessarily the weakest bridges nor the bridges with the highest pre-earthquake traffic volume. Instead, bridges at moderately high seismic risk on non-redundant routes play a particularly critical role.

Keywords: Civil and Environmental Engineering.
Advisor: Baker Jack W. primary advisor. Thesis advisor
Kiremidjian Anne S. (Anne Setian) advisor. Thesis advisor
Song Junho