Security and Trust in Distributed Computation

We propose three research problems to explore the relations between trust and security in the setting of distributed computation. In the first problem, we study trust-based adversary detection in distributed consensus computation. The adversaries we consider behave arbitrarily disobeying the consensus protocol. We propose a trust-based consensus algorithm with local and global trust evaluations. The algorithm can be abstracted using a two-layer structure with the top layer running a trust-based consensus algorithm and the bottom layer as a subroutine executing a global trust update scheme. We utilize a set of pre-trusted nodes, headers, to propagate local trust opinions throughout the network. This two-layer framework is flexible in that it can be easily extensible to contain more complicated decision rules, and global trust schemes. The first problem assumes that normal nodes are homogeneous, i.e. it is guaranteed that a normal node always behaves as it is programmed. In the second and third problems however, we assume that nodes are heterogeneous, i.e, given a task, the probability that a node generates a correct answer varies from node to node. The adversaries considered in these two problems are workers from the open crowd who are either investing little efforts in the tasks assigned to them or intentionally give wrong answers to questions. In the second part of the thesis, we consider a typical crowdsourcing task that aggregates input from multiple workers as a problem in information fusion. To cope with the issue of noisy and sometimes malicious input from workers, trust is used to model workers' expertise. In a multi-domain knowledge learning task, however, using scalar-valued trust to model a worker's performance is not sufficient to reflect the worker's trustworthiness in each of the domains. To address this issue, we propose a probabilistic model to jointly infer multi-dimensional trust of workers, multi-domain properties of questions, and true labels of questions. Our model is very flexible and extensible to incorporate metadata associated with questions. To show that, we further propose two extended models, one of which handles input tasks with real-valued features and the other handles tasks with text features by incorporating topic models. Our models can effectively recover trust vectors of workers, which can be very useful in task assignment adaptive to workers' trust in the future. These results can be applied for fusion of information from multiple data sources like sensors, human input, machine learning results, or a hybrid of them. In the second subproblem, we address crowdsourcing with adversaries under logical constraints. We observe that questions are often not independent in real life applications. Instead, there are logical relations between them. Similarly, workers that provide answers are not independent of each other either. Answers given by workers with similar attributes tend to be correlated. Therefore, we propose a novel unified graphical model consisting of two layers. The top layer encodes domain knowledge which allows users to express logical relations using first-order logic rules and the bottom layer encodes a traditional crowdsourcing graphical model. Our model can be seen as a generalized probabilistic soft logic framework that encodes both logical relations and probabilistic dependencies. To solve the collective inference problem efficiently, we have devised a scalable joint inference algorithm based on the alternating direction method of multipliers. The third part of the thesis considers the problem of optimal assignment under budget constraints when workers are unreliable and sometimes malicious. In a real crowdsourcing market, each answer obtained from a worker incurs cost. The cost is associated with both the level of trustworthiness of workers and the difficulty of tasks. Typically, access to expert-level (more trustworthy) workers is more expensive than to average crowd and completion of a challenging task is more costly than a click-away question. In this problem, we address the problem of optimal assignment of heterogeneous tasks to workers of varying trust levels with budget constraints. Specifically, we design a trust-aware task allocation algorithm that takes as inputs the estimated trust of workers and pre-set budget, and outputs the optimal assignment of tasks to workers. We derive the bound of total error probability that relates to budget, trustworthiness of crowds, and costs of obtaining labels from crowds naturally. Higher budget, more trustworthy crowds, and less costly jobs result in a lower theoretical bound. Our allocation scheme does not depend on the specific design of the trust evaluation component. Therefore, it can be combined with generic trust evaluation algorithms.

King of the Renaissance: Art and Politics at the Neapolitan Court of Ferrante I, 1458-1494

In the second half of the fifteenth century, King Ferrante I of Naples (r. 1458-1494) dominated the political and cultural life of the Mediterranean world. His court was home to artists, writers, musicians, and ambassadors from England to Egypt and everywhere in between. Yet, despite its historical importance, Ferrante’s court has been neglected in the scholarship. This dissertation provides a long-overdue analysis of Ferrante’s artistic patronage and attempts to explicate the king’s specific role in the process of art production at the Neapolitan court, as well as the experiences of artists employed therein. By situating Ferrante and the material culture of his court within the broader discourse of Early Modern art history for the first time, my project broadens our understanding of the function of art in Early Modern Europe. I demonstrate that, contrary to traditional assumptions, King Ferrante was a sophisticated patron of the visual arts whose political circumstances and shifting alliances were the most influential factors contributing to his artistic patronage. Unlike his father, Alfonso the Magnanimous, whose court was dominated by artists and courtiers from Spain, France, and elsewhere, Ferrante differentiated himself as a truly Neapolitan king. Yet Ferrante’s court was by no means provincial. His residence, the Castel Nuovo in Naples, became the physical embodiment of his commercial and political network, revealing the accretion of local and foreign visual vocabularies that characterizes Neapolitan visual culture.

Heritage Language Maintenance and Biliteracy Development for Immigrants' Children: A Study of Chinese Immigrants' Family Language Policy and Biliteracy Practices

This study reports on research that examines the family language policy (FLP) and biliteracy practices of middle-class Chinese immigrant families in a metropolitan area in the southwest of the U.S. by exploring language practices pattern among family members, language and literacy environment at home, parents’ language management, parents’ language attitudes and ideologies, and biliteracy practices. In this study, I employed mixed methods, including survey and interviews, to investigate Chinese immigrant parents’ FLP, biliteracy practices, their life stories, and their experience of raising and nurturing children in an English-dominant society. Survey questionnaires were distributed to 55 Chinese immigrant parents and interviews were conducted with five families, including mothers and children. One finding from this study is that the language practices pattern at home shows the trend of language shift among the Chinese immigrants’ children. Children prefer speaking English with parents, siblings, and peers, and home literacy environment for children manifests an English-dominant trend. Chinese immigrant parents’ language attitudes and ideologies are largely influenced by English-only ideology. The priority for learning English surpasses the importance of Chinese learning, which is demonstrated by the English-dominant home literacy practices and an English-dominant language policy. Parents invest more in English literacy activities and materials for children, and very few parents implement Chinese-only policy for their children. A second finding from this study is that a multitude of factors from different sources shape and influence Chinese immigrants’ FLP and biliteracy practices. The factors consist of family-related factors, social factors, linguistic factors, and individual factors. A third finding from this study is that a wide variety of strategies are adopted by Chinese immigrant families, which have raised quite balanced bilingual children, to help children maintain Chinese heritage language (HL) and develop both English and Chinese literacy. The close examination and comparison of different families with English monolingual children, with children who have limited knowledge of HL, and with quite balanced bilingual children, this study discovers that immigrant parents, especially mothers, play a fundamental and irreplaceable role in their children’s HL maintenance and biliteracy development and it recommends to immigrant parents in how to implement the findings of this study to nurture their children to become bilingual and biliterate. Due to the limited number and restricted area and group of participant sampling, the results of this study may not be generalized to other groups in different contexts.

JOINT ENERGY BEAMFORMING AND TIME ASSIGNMENT FOR COOPERATIVE WIRELESS POWERED NETWORKS

Wireless power transfer (WPT) and radio frequency (RF)-based energy har- vesting arouses a new wireless network paradigm termed as wireless powered com- munication network (WPCN), where some energy-constrained nodes are enabled to harvest energy from the RF signals transferred by other energy-sufficient nodes to support the communication operations in the network, which brings a promising approach for future energy-constrained wireless network design. In this paper, we focus on the optimal WPCN design. We consider a net- work composed of two communication groups, where the first group has sufficient power supply but no available bandwidth, and the second group has licensed band- width but very limited power to perform required information transmission. For such a system, we introduce the power and bandwidth cooperation between the two groups so that both group can accomplish their expected information delivering tasks. Multiple antennas are employed at the hybrid access point (H-AP) to en- hance both energy and information transfer efficiency and the cooperative relaying is employed to help the power-limited group to enhance its information transmission throughput. Compared with existing works, cooperative relaying, time assignment, power allocation, and energy beamforming are jointly designed in a single system. Firstly, we propose a cooperative transmission protocol for the considered system, where group 1 transmits some power to group 2 to help group 2 with information transmission and then group 2 gives some bandwidth to group 1 in return. Sec- ondly, to explore the information transmission performance limit of the system, we formulate two optimization problems to maximize the system weighted sum rate by jointly optimizing the time assignment, power allocation, and energy beamforming under two different power constraints, i.e., the fixed power constraint and the aver- age power constraint, respectively. In order to make the cooperation between the two groups meaningful and guarantee the quality of service (QoS) requirements of both groups, the minimal required data rates of the two groups are considered as constraints for the optimal system design. As both problems are non-convex and have no known solutions, we solve it by using proper variable substitutions and the semi-definite relaxation (SDR). We theoretically prove that our proposed solution method can guarantee to find the global optimal solution. Thirdly, consider that the WPCN has promising application potentials in future energy-constrained net- works, e.g., wireless sensor network (WSN), wireless body area network (WBAN) and Internet of Things (IoT), where the power consumption is very critical. We investigate the minimal power consumption optimal design for the considered co- operation WPCN. For this, we formulate an optimization problem to minimize the total consumed power by jointly optimizing the time assignment, power allocation, and energy beamforming under required data rate constraints. As the problem is also non-convex and has no known solutions, we solve it by using some variable substitutions and the SDR method. We also theoretically prove that our proposed solution method for the minimal power consumption design guarantees the global optimal solution. Extensive experimental results are provided to discuss the system performance behaviors, which provide some useful insights for future WPCN design. It shows that the average power constrained system achieves higher weighted sum rate than the fixed power constrained system. Besides, it also shows that in such a WPCN, relay should be placed closer to the multi-antenna H-AP to achieve higher weighted sum rate and consume lower total power.