Information Leakage Measurement and Prevention in Anonymous Traffic

University of Minnesota Ph.D. dissertation. June 2019. Major: Computer Science. Advisor: Nick Hopper. 1 computer file (PDF); viii, 76 pages.The pervasive Internet surveillance and the wide-deployment of Internet censors lead to the need for making traffic anonymous. However, recent studies demonstrate the information leakage in anonymous traffic that can be used to de-anonymize Internet users. This thesis focuses on how to measure and prevent such information leakage in anonymous traffic. Choosing Tor anonymous networks as the target, the first part of this thesis conducts the first large-scale information leakage measurement in anonymous traffic and discovers that the popular practice of validating WF defenses by accuracy alone is flawed. We make this measurement possible by designing and implementing our website fingerprint density estimation (WeFDE) framework. The second part of this thesis focuses on preventing such information leakage. Specifically, we design two anti-censorship systems which are able to survive traffic analysis and provide unblocked online video watching and social networking

Building Blocks for IoT Analytics Internet-of-Things Analytics

Internet-of-Things (IoT) Analytics are an integral element of most IoT applications, as it provides the means to extract knowledge, drive actuation services and optimize decision making. IoT analytics will be a major contributor to IoT business value in the coming years, as it will enable organizations to process and fully leverage large amounts of IoT data, which are nowadays largely underutilized. The Building Blocks of IoT Analytics is devoted to the presentation the main technology building blocks that comprise advanced IoT analytics systems. It introduces IoT analytics as a special case of BigData analytics and accordingly presents leading edge technologies that can be deployed in order to successfully confront the main challenges of IoT analytics applications. Special emphasis is paid in the presentation of technologies for IoT streaming and semantic interoperability across diverse IoT streams. Furthermore, the role of cloud computing and BigData technologies in IoT analytics are presented, along with practical tools for implementing, deploying and operating non-trivial IoT applications. Along with the main building blocks of IoT analytics systems and applications, the book presents a series of practical applications, which illustrate the use of these technologies in the scope of pragmatic applications. Technical topics discussed in the book include: Cloud Computing and BigData for IoT analyticsSearching the Internet of ThingsDevelopment Tools for IoT Analytics ApplicationsIoT Analytics-as-a-ServiceSemantic Modelling and Reasoning for IoT AnalyticsIoT analytics for Smart BuildingsIoT analytics for Smart CitiesOperationalization of IoT analyticsEthical aspects of IoT analyticsThis book contains both research oriented and applied articles on IoT analytics, including several articles reflecting work undertaken in the scope of recent European Commission funded projects in the scope of the FP7 and H2020 programmes. These articles present results of these projects on IoT analytics platforms and applications. Even though several articles have been contributed by different authors, they are structured in a well thought order that facilitates the reader either to follow the evolution of the book or to focus on specific topics depending on his/her background and interest in IoT and IoT analytics technologies. The compilation of these articles in this edited volume has been largely motivated by the close collaboration of the co-authors in the scope of working groups and IoT events organized by the Internet-of-Things Research Cluster (IERC), which is currently a part of EU's Alliance for Internet of Things Innovation (AIOTI)

Toward Open and Programmable Wireless Network Edge

Increasingly, the last hop connecting users to their enterprise and home networks is wireless. Wireless is becoming ubiquitous not only in homes and enterprises but in public venues such as coffee shops, hospitals, and airports. However, most of the publicly and privately available wireless networks are proprietary and closed in operation. Also, there is little effort from industries to move forward on a path to greater openness for the requirement of innovation. Therefore, we believe it is the domain of university researchers to enable innovation through openness. In this thesis work, we introduce and defines the importance of open framework in addressing the complexity of the wireless network. The Software Defined Network (SDN) framework has emerged as a popular solution for the data center network. However, the promise of the SDN framework is to make the network open, flexible and programmable. In order to deliver on the promise, SDN must work for all users and across all networks, both wired and wireless. Therefore, we proposed to create new modules and APIs to extend the standard SDN framework all the way to the end-devices (i.e., mobile devices, APs). Thus, we want to provide an extensible and programmable abstraction of the wireless network as part of the current SDN-based solution. In this thesis work, we design and develop a framework, weSDN (wireless extension of SDN), that extends the SDN control capability all the way to the end devices to support client-network interaction capabilities and new services. weSDN enables the control-plane of wireless networks to be extended to mobile devices and allows for top-level decisions to be made from an SDN controller with knowledge of the network as a whole, rather than device centric configurations. In addition, weSDN easily obtains user application information, as well as the ability to monitor and control application flows dynamically. Based on the weSDN framework, we demonstrate new services such as application-aware traffic management, WLAN virtualization, and security management

Building Blocks for IoT Analytics Internet-of-Things Analytics

Internet-of-Things (IoT) Analytics are an integral element of most IoT applications, as it provides the means to extract knowledge, drive actuation services and optimize decision making. IoT analytics will be a major contributor to IoT business value in the coming years, as it will enable organizations to process and fully leverage large amounts of IoT data, which are nowadays largely underutilized. The Building Blocks of IoT Analytics is devoted to the presentation the main technology building blocks that comprise advanced IoT analytics systems. It introduces IoT analytics as a special case of BigData analytics and accordingly presents leading edge technologies that can be deployed in order to successfully confront the main challenges of IoT analytics applications. Special emphasis is paid in the presentation of technologies for IoT streaming and semantic interoperability across diverse IoT streams. Furthermore, the role of cloud computing and BigData technologies in IoT analytics are presented, along with practical tools for implementing, deploying and operating non-trivial IoT applications. Along with the main building blocks of IoT analytics systems and applications, the book presents a series of practical applications, which illustrate the use of these technologies in the scope of pragmatic applications. Technical topics discussed in the book include: Cloud Computing and BigData for IoT analyticsSearching the Internet of ThingsDevelopment Tools for IoT Analytics ApplicationsIoT Analytics-as-a-ServiceSemantic Modelling and Reasoning for IoT AnalyticsIoT analytics for Smart BuildingsIoT analytics for Smart CitiesOperationalization of IoT analyticsEthical aspects of IoT analyticsThis book contains both research oriented and applied articles on IoT analytics, including several articles reflecting work undertaken in the scope of recent European Commission funded projects in the scope of the FP7 and H2020 programmes. These articles present results of these projects on IoT analytics platforms and applications. Even though several articles have been contributed by different authors, they are structured in a well thought order that facilitates the reader either to follow the evolution of the book or to focus on specific topics depending on his/her background and interest in IoT and IoT analytics technologies. The compilation of these articles in this edited volume has been largely motivated by the close collaboration of the co-authors in the scope of working groups and IoT events organized by the Internet-of-Things Research Cluster (IERC), which is currently a part of EU's Alliance for Internet of Things Innovation (AIOTI)

Index to 1981 NASA Tech Briefs, volume 6, numbers 1-4

Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1981 Tech Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

The density and peculiar velocity fields of nearby galaxies

We review the quantitative science that can be and has been done with redshift and peculiar velocity surveys of galaxies in the nearby universe. After a brief background setting the cosmological context for this work, the first part of this review focuses on redshift surveys. The practical issues of how redshift surveys are carried out, and how one turns a distribution of galaxies into a smoothed density field, are discussed. Then follows a description of major redshift surveys that have been done, and the local cosmography out to 8,000 km/s that they have mapped. We then discuss in some detail the various quantitative cosmological tests that can be carried out with redshift data. The second half of this review concentrates on peculiar velocity studies, beginning with a thorough review of existing techniques. After discussing the various biases which plague peculiar velocity work, we survey quantitative analyses done with peculiar velocity surveys alone, and finally with the combination of data from both redshift and peculiar velocity surveys. The data presented rule out the standard Cold Dark Matter model, although several variants of Cold Dark Matter with more power on large scales fare better. All the data are consistent with the hypothesis that the initial density field had a Gaussian distribution, although one cannot rule out broad classes of non-Gaussian models. Comparison of the peculiar velocity and density fields constrains the Cosmological Density Parameter. The results here are consistent with a flat universe with mild biasing of the galaxies relative to dark matter, although open universe models are by no means ruled out.Comment: In press, Physics Reports. 153 pages. gzip'ed postscript of text plus 20 embedded figures. Also available via anonymous ftp at ftp://eku.ias.edu/pub/strauss/review/physrep.p

DEVELOPMENT AND CONTROL OF PERSONAL MOBILITY PLATFORM FOR MULTI-HIERARCHY LAST MILE TRANSPORTATION

Ph.DDOCTOR OF PHILOSOPH

Modular wireless networks for infrastructure-challenged environments

While access to Internet and cellular connectivity is easily achieved in densely-populated areas, provisioning of communication services is much more challenging in remote rural areas. At the same time Internet access is of critical importance to residents of such rural communities. People's curiosity and realization of the opportunities provided by Internet and cellular access is the key ingredient to adoption. However, poor network performance can easily impede the process of adoption by discouraging people to access and use connectivity. With this in mind, we evaluate performance and adoption of various connectivity technologies in rural developing regions and identify avenues that need immediate attention to guarantee smoother technology adoption. In light of this analysis we propose novel system designs that meet these needs. In this thesis we focus on cellular and broadband Internet connectivity. Commercial cellular networks are highly centralized, which requires costly backhaul. This, coupled with high price for equipment, maintenance and licensing renders cellular network access commercially-infeasible in rural areas. At the same time rural cellular communications are highly local: 70% of the rural-residential calls have an originator-destination pair within the same antenna. In line with this observation we design a low-cost cellular network architecture dubbed Kwiizya, to provide local voice and text messaging services in a rural community. Where outbound connectivity is available, Kwiizya can provide global services. While commercial networks are becoming more available in rural areas they are often out of financial reach of rural residents. Furthermore, these networks typically provide only basic voice and SMS services and no mobile data. To address these challenges, our proposed work allows Kwiizya to operate in coexistence with commercial cellular networks in order to extend local coverage and provide more advanced services that are not delivered by the commercial networks. Internet connectivity in rural areas is typically provided through slow satellite links. The challenges in performance and adoption of such networks have been previously studied. We add a unique dataset and consequent analysis to this spectrum of work, which captures the upgrade of the gateway connectivity in the rural community of Macha, Zambia from a 256kbps satellite link to a more capable 2Mbps terrestrial link. We show that the improvement in performance and user experience is not necessarily proportional to the bandwidth increase. While this increase improved the network usability, it also opened opportunities for adoption of more demanding services that were previously out of reach. As a result the network performance was severely degraded over the long term. To address these challenges we employ white space communication both for connectivity to more capable remote gateways, as well as for end user connectivity. We develop VillageLink, a distributed method that optimizes channel allocation to maximize throughput and enables both remote gateway access as well as end user coverage. While VillageLink features lightweight channel probing, we also consider external sources of channel availability. We design a novel approach for estimation of channel occupancy called TxMiner, which is capable of extracting transmitter characteristics from raw spectrum measurements. We study the adoption and implications of network connectivity in rural communities. In line with the results of our analyses we design and build system architectures that are geared to meet critical needs in these communities. While the focus of analysis in this thesis is on rural sub-Saharan Africa, the proposed designs and system implementations are more general and can serve in infrastructure-challenged communities across the world