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关键词： Design   Psychology   Computer science  

摘要： Augmented and mixed reality experiences are increasingly accessible due to advances in technology in both professional and daily settings. Technology continues to evolve into multiple different forms, including tablet experiences in the form of augmented reality (AR) and mixed reality (MR) using wearable heads-up displays (HUDs). Currently, standards for best usability practices continue to evolve for MR HUD two-dimensional user interfaces (2D UI) and three-dimensional user interfaces (3D UI). Therefore, research on evolving usability practices will serve as guidance for future development of MR HUD applications. The objective of this dissertation is to understand what gestures users intuitively make to respond to a MR environment while wearing a HUD. The Microsoft HoloLens is a wearable HUD that can be used for MR. The Microsoft HoloLens contains two core gestures that were developed to interact with holographic interfaces in MR. Although current gestures can be learned to generate successful outcomes, this dissertation provides a better understanding of which gestures are intuitive to new users of a MR environment. To understand which gestures are intuitive to users, 74 participants without any experience with MR attempted to make gestures within a wearable MR HUD environment. The results of this study show that previous technology experience can influence gesture choice; however, gesture choice also depends on the goal of the interaction scenario. Results suggest that a greater number of programmed gestures are needed in order to best utilize all tools available in wearable HUDs in MR. Results of this dissertation suggest that five new gestures should be created, with three of these gestures serving to reflect a connection between MR interaction and current gesture-based technology. Additionally, results suggest that two new gestures should be created that reflect a connection between gestures for MR and daily movements in the physical world space.

关键词： Artificial intelligence   Computer science  

摘要： Understanding others is a deeply human urge basic in our existential quest. It requires knowing where someone has come from and where they sit amongst peers. Phylogenetic analysis and genome wide association studies seek to tell us where we’ve come from and where we are relative to one another through evolutionary history and genetic makeup. Current methods do not address the computational complexity caused by new forms of genomic data, namely long-read DNA sequencing and increased abundances of assembled genomes, that are becoming evermore abundant. To address this, we explore specialized data structures for storing and comparing genomic information. This work resulted in the creation of novel data structures for storing multiple genomes that can be used for identifying structural variations and other types of polymorphisms. Using these methods we illuminate the genetic history of organisms in our efforts to understand the world around us.

关键词： Computer science  

摘要： Online social networks have gained tremendous popularity recently. Millions of people use social network apps to share precious moments with friends and family. Users are often asked to provide personal information such as name, gender, address when using social networks. This information could be collected, analyzed, and re-published at large scale for both academic and business studies, and are usually processed by anonymization methods to protect user's privacy. However, these anonymized data could be misused by unauthorized third parties and even attackers to violate users' privacy. Several structure-based de-anonymization techniques have been proposed to re-identify the users in anonymized networks. In light of this, we first address the novel problems of re-identifying users in anonymized social networks with the help of public user attributes in this work. More specifically, we quantify the significance of attributes in a social network, based on which we propose an attribute-based similarity measure; then we design an algorithm by exploiting attribute-based similarity to de-anonymize social network data; finally we employ the dataset collected from a real-world online social network to evaluate our method. And experimental results show that public user attributes can significantly improve the de-anonymization accuracy. Extensive researches on anonymization techniques have been carried out to protect the data from privacy violations in social networks. Nevertheless, anonymization may affect the usability of the data as random noises are introduced, decreasing user experience. Therefore, a trade-off between privacy protection and data usability must be sought. In this work, we employ various graph and application utility metrics to investigate this trade-off. More specifically, we conduct an empirical study by implementing five state-of-the-art anonymization algorithms to analyze the graph and application utilities on a Facebook and a Twitter dataset. Our resu

关键词： Computer science  

摘要： The lack of fungibility in Bitcoin has forced its userbase to seek out tools that can heighten their anonymity. Third-party Bitcoin mixers utilize obfuscation techniques to protect participants from blockchain analysis. In recent years, various centralized and decentralized Bitcoin mixing implementations have been proposed in academic literature. Although these methods depict a threat-free environment for users to preserve their anonymity, public Bitcoin mixers continue to be associated with theft and poor implementation. This research explores the public Bitcoin mixer ecosystem to identify if today's mixing services have adopted academically proposed solutions. This is done through real-world interactions with publicly available mixers to analyze both implementation and resistance to common threats in the mixing landscape. First, proposed decentralized and centralized mixing protocols found in literature are outlined. Then, data is presented from 19 publicly announced mixing services available on the deep web and clearnet. The services are categorized based on popularity with the Bitcoin community and experiments are conducted on five public mixing services: ChipMixer, MixTum, Bitcoin Mixer, CryptoMixer, and Sudoku Wallet. The results of the experiments highlight a clear gap between public and proposed Bitcoin mixers in both implementation and security. Today's mixing services focus on presenting users with a false sense of control to gain their trust rather then employing secure mixing techniques. As a result, the five selected services lack implementation of academically proposed techniques and display poor resistance to common mixer-related threats.

关键词： Computer science  

摘要： Optimizing nested loops has been considered as an important topic and widely studied in parallel programming. With the development of GPU architectures, the performance of these computations can be significantly boosted with the massively parallel hardware. General matrix-matrix multiplication is a typical example where executing such an algorithm on GPUs outperforms the performance obtained on other multicore CPUs. However, achieving ideal performance on GPUs usually requires a lot of human effort to manage the massively parallel computation resources. Therefore, the efficient implementation of optimizing nested loops on GPUs became a popular topic in recent years. We present our work based on the tiling strategy in this dissertation to address three kinds of popular problems. Different kinds of computations bring in different latency issues where dependencies in the computation may result in insufficient parallelism and the performance of computations without dependencies may be degraded due to intensive memory accesses. In this thesis, we tackle the challenges for each kind of problem and believe that other computations performed in nested loops can also benefit from the presented techniques. We improve a parallel approximation algorithm for the problem of scheduling jobs on parallel identical machines to minimize makespan with a high-dimensional tiling method. The algorithm is designed and optimized for solving this kind of problem efficiently on GPUs. Because the algorithm is based on a higher-dimensional dynamic programming approach, where dimensionality refers to the number of variables in the dynamic programming equation characterizing the problem, the existing implementation suffers from the pain of dimensionality and cannot fully utilize GPU resources. We design a novel data-partitioning technique to accelerate the higher-dimensional dynamic programming component of the algorithm. Both the load imbalance and exceeding memory capacity issues are addressed i

关键词： Computer science  

摘要： Machine learning related applications and research have sparked global interest in recent years. Exciting advances have been witnessed in this field. However, this promising domain has long been suffering from unaffordable computational costs due to the inherent complexity of machine learning models. The problem is becoming only more significant as dataset sizes keep growing. This dissertation introduces redundancy-reduced algorithm design, a new approach to address the issue. It centers the algorithm design around the removal of unnecessary computations. Unlike approximation algorithms, redundancy-reduced algorithms strictly preserve the semantics of the original algorithms, and hence the quality of the machine learning results. To build a redundancy-reduced algorithm, there are three fundamental questions: (1) What computations are redundant? (2) How to effectively identify and remove them? (3) How to maximize the number of identified redundant computations and minimize the identification overhead? This dissertation gives a systematic study of the questions on three widely used machine learning algorithms that correspond to three representative scenarios in machine learning: classification, clustering and hyper-parameter tuning. Specifically, it proposes FALCON, LEEM and SDPC, which are three redundancy-reduced algorithms for Citation KNN, Elastic EM and Density Peak Clustering, respectively. It proposes a set of strategies for customizing the algorithm design based on the characteristics of each individual algorithm to tap into the full potential. The strategies include exploitation of lower and upper bounds, computation filtering, computation reordering, results reuse, and so on. Experiments on various datasets have repeatedly confirmed the significant benefits of redundancy-reduced algorithm designs, yielding several times to several orders of magnitude of speedups. Browse the emoji picker to find the best characters easily. Sort by category or search by name.

关键词： Information technology   Computer science  

摘要： Corporate Information Security (IS) organizations have a growing need to move towards strategic, risk-aligned governance to address the risk to the enterprise. Research has shown that modern IS departments suffer wasted and inconsistent resources due to ad-hoc processes and lack of alignment with business objectives. Information Security Governance (ISG) is a strategic discipline to address the effective governance and allocation of these critical IS resources. This study investigated the relationship between the strategic components of Information Security Governance (ISG), and prior research based on a conceptual framework representing the convergence of ISG with enterprise risk management (ERM) and enterprise security architecture (ESA). The research propositions sought this convergence as the ideal state for strategic, risk-driven security governance. Based on a review of scholarly literature, a phenomenological study was constructed to investigate strategy-driven ISG. Field interviews were conducted with twenty cybersecurity experts across North America, with Chief Information Security Officers (CISOs) representing the most significant percentage of participants. The analysis of the interview data was filtered through axial coding for anonymity and thematic evaluation, with the themes of real-world governance benefits and challenges quickly emerging. Considerations surrounding waste reduction, proactive security posture, risk-driven planning, and architectural security planning were predominantly evident in the findings. The results indicated that security governance plays a pivotal role in the effective allocation of IS resources and is a reliable indicator of program maturity. Additionally, strategic planning and architectural techniques can optimize IS planning for addressing the highest degree of risk within our digital economy.

关键词： Information technology   Computer science  

摘要： As was observed during the 2014 Target security breach and the global 2017 Wannacry ransomware attack, information security policy noncompliance can have dire consequences, not only on the secured private information but on the finances of the organizations that are attacked. Information security policy noncompliance is the most significant risk to organizational security, but risk assessment models are insufficient to address emerging threats and the current body of research lacks investigations into actual noncompliant behaviors perpetrated by non-IT personnel. The purpose of this qualitative phenomenological study was to investigate the lived experiences of 24 Department of Defense level IT professionals to identify specific noncompliant behaviors of organizational personnel. The conceptual framework of the study was cyber physical systems security, which encompasses all physical, hardware, and software domains within any given IT/IS implementation. Qualitative analysis of the collected interview data yielded 5 thematic categories that contain distinct patterns of policy noncompliance and antecedents to noncompliant behaviors: convenience noncompliance, lack of education or awareness, noncompliance due to human nature, leadership noncompliance, and misinterpretation of policy. Data saturation was achieved. It is recommended that the results be used to create compliance models based on human experiences, to create quantitative instruments and studies, to design experimental or causal studies, to contribute to risk assessment models, and to apply to cyber physical systems security models.

关键词： Computer science  

摘要： Java is one of the most widely used programming languages. However, the absence of explicit support for architectural constructs, such as software components, in the programming language itself has prevented software developers from achieving the many benefits that come with architecture-based development. To address this issue, Java 9 has introduced the Java Platform Module System (JPMS), resulting in the first instance of encapsulation of modules with rich software architectural interfaces added to a mainstream programming language. The primary goal of JPMS is to construct and maintain large applications efficiently—as well as improve the encapsulation, security, and maintainability of Java applications in general and the JDK itself. A challenge, however, is that module declarations do not necessarily reflect actual usage of modules in an application, allowing developers to mistakenly specify inconsistent dependencies among the modules. In this paper, we formally define 8 inconsistent modular dependencies that may arise in Java-9 applications. We also present Darcy, an approach that leverages these definitions and static program analyses to automatically (1) detect the specified inconsistent dependencies within Java applications and (2) repair those identified inconsistencies. The results of our experiments, conducted over 38 open-source Java-9 applications, indicate that architectural inconsistencies are widespread and demonstrate the benefits of Darcy in automated detection and repair of these inconsistencies.

关键词： Computer science  

摘要： Micro aerial vehicles a.k.a. drones, have become an integral part of a variety of civilian and military application domains, including but not limited to aerial surveying and mapping, aerial surveillance and security, aerial inspection of infrastructure, and aerial delivery. Meanwhile, the cybersecurity of drones is gaining significant attention due to both financial and strategic information and value involved in aerial applications. As a result of the lack of security features in the communication protocol, an adversary can easily interfere with on-going communications or even seize control of the drone. In this thesis, we propose a lightweight digital signature protocol, also referred to as DroneSig, to protect drones from a man-in-the-middle attack, where an adversary eavesdrops the communication between Ground Control Station (GCS) and drone, and impersonates the GCS and sends fake commands to terminate the on-going mission or even take control over the drone. The basic idea of the DroneSig is that the drone will only execute the new command after validating the received digital signature from the GCS, proving that the new command message is coming from the authenticated GCS. If the validation of the digital signature fails, the new command is rejected immediately, and the Return-to-Launch (RTL) mode is initiated and forces the drone to return to the take-off position. We conduct extensive simulation experiments for performance evaluation and comparison using OMNeT++, and simulation results show that the proposed lightweight digital signature protocol achieves better performance in terms of energy consumption and computation time compared to the standard Advanced Encryption Standard (AES) cryptographic technique.