Privacy Leakage through Sensory Data on Smart Devices

Mobile devices are becoming more and more indispensable in people’s daily life. They bring variety of conveniences. However, many privacy issues also arise along with the ubiquitous usage of smart devices. Nowadays, people rely on smart devices for business and work, thus much sensitive information is released. Although smart device manufactures spend much effort to provide system level strategies for privacy preservation, lots of studies have shown that these strategies are far from perfect. In this dissertation, many privacy risks are explored. Smart devices are becoming more and more powerful as more and more sensors are embedded into smart devices. In this thesis, the relationship between sensory data and a user’s location information is analyzed first. A novel inference model and a corresponding algorithm are proposed to infer a user’s location information solely based on sensory data. The proposed approach is validated towards real-world sensory data. Another privacy issue investigated in this thesis is the inference of user behaviors based on sensory data. From extensive experiment results, it is observed that there is a strong correlation between sensory data and the tap position on a smart device’s screen. A sensory data collection app is developed to collect sensory data from more than 100 volunteers. A conventional neural network based method is proposed to infer a user’s input on a smart phone. The proposed inference model and algorithm are compared with several previous methods through extensive experiments. The results show that our method has much better accuracy. Furthermore, based on this inference model, several possible ways to steal private information are illustrated

Elastic Highly Available Cloud Computing

High availability and elasticity are two the cloud computing services technical features. Elasticity is a key feature of cloud computing where provisioning of resources is closely tied to the runtime demand. High availability assure that cloud applications are resilient to failures. Existing cloud solutions focus on providing both features at the level of the virtual resource through virtual machines by managing their restart, addition, and removal as needed. These existing solutions map applications to a specific design, which is not suitable for many applications especially virtualized telecommunication applications that are required to meet carrier grade standards. Carrier grade applications typically rely on the underlying platform to manage their availability by monitoring heartbeats, executing recoveries, and attempting repairs to bring the system back to normal. Migrating such applications to the cloud can be particularly challenging, especially if the elasticity policies target the application only, without considering the underlying platform contributing to its high availability (HA). In this thesis, a Network Function Virtualization (NFV) framework is introduced; the challenges and requirements of its use in mobile networks are discussed. In particular, an architecture for NFV framework entities in the virtual environment is proposed. In order to reduce signaling traffic congestion and achieve better performance, a criterion to bundle multiple functions of virtualized evolved packet-core in a single physical device or a group of adjacent devices is proposed. The analysis shows that the proposed grouping can reduce the network control traffic by 70 percent. Moreover, a comprehensive framework for the elasticity of highly available applications that considers the elastic deployment of the platform and the HA placement of the application’s components is proposed. The approach is applied to an internet protocol multimedia subsystem (IMS) application and demonstrate how, within a matter of seconds, the IMS application can be scaled up while maintaining its HA status

An energy-aware scheduling approach for resource-intensive jobs using smart mobile devices as resource providers

The ever-growing adoption of smart mobile devices is a worldwide phenomenon that positions smart-phones and tablets as primary devices for communication and Internet access. In addition to this, the computing capabilities of such devices, often underutilized by their owners, are in continuous improvement. Today, smart mobile devices have multi-core CPUs, several gigabytes of RAM, and ability to communicate through several wireless networking technologies. These facts caught the attention of researchers who have proposed to leverage smart mobile devices aggregated computing capabilities for running resource intensive software. However, such idea is conditioned by key features, named singularities in the context of this thesis, that characterize resource provision with smart mobile devices.These are the ability of devices to change location (user mobility), the shared or non-dedicated nature of resources provided (lack of ownership) and the limited operation time given by the finite energy source (exhaustible resources).Existing proposals materializing this idea differ in the singularities combinations they target and the way they address each singularity, which make them suitable for distinct goals and resource exploitation opportunities. The latter are represented by real life situations where resources provided by groups of smart mobile devices can be exploited, which in turn are characterized by a social context and a networking support used to link and coordinate devices. The behavior of people in a given social context configure a special availability level of resources, while the underlying networking support imposes restrictionson how information flows, computational tasks are distributed and results are collected. The latter constitutes one fundamental difference of proposals mainly because each networking support ?i.e., ad-hoc and infrastructure based? has its own application scenarios. Aside from the singularities addressed and the networking support utilized, the weakest point of most of the proposals is their practical applicability. The performance achieved heavily relies on the accuracy with which task information, including execution time and/or energy required for execution, is provided to feed the resource allocator.The expanded usage of wireless communication infrastructure in public and private buildings, e.g., shoppings, work offices, university campuses and so on, constitutes a networking support that can be naturally re-utilized for leveraging smart mobile devices computational capabilities. In this context, this thesisproposal aims to contribute with an easy-to-implement  scheduling approach for running CPU-bound applications on a cluster of smart mobile devices. The approach is aware of the finite nature of smart mobile devices energy, and it does not depend on tasks information to operate. By contrast, it allocatescomputational resources to incoming tasks using a node ranking-based strategy. The ranking weights nodes combining static and dynamic parameters, including benchmark results, battery level, number of queued tasks, among others. This node ranking-based task assignment, or first allocation phase, is complemented with a re-balancing phase using job stealing techniques. The second allocation phase is an aid to the unbalanced load provoked as consequence of the non-dedicated nature of smart mobile devices CPU usage, i.e., the effect of the owner interaction, tasks heterogeneity, and lack of up-to-dateand accurate information of remaining energy estimations. The evaluation of the scheduling approach is through an in-vitro simulation. A novel simulator which exploits energy consumption profiles of real smart mobile devices, as well as, fluctuating CPU usage built upon empirical models, derived from real users interaction data, is another major contribution. Tests that validate the simulation tool are provided and the approach is evaluated in scenarios varying the composition of nodes, tasks and nodes characteristics including different tasks arrival rates, tasks requirements and different levels of nodes resource utilization.Fil: Hirsch Jofré, Matías Eberardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentin

Heterogeneous Cloud Systems Based on Broadband Embedded Computing

Computing systems continue to evolve from homogeneous systems of commodity-based servers within a single data-center towards modern Cloud systems that consist of numerous data-center clusters virtualized at the infrastructure and application layers to provide scalable, cost-effective and elastic services to devices connected over the Internet. There is an emerging trend towards heterogeneous Cloud systems driven from growth in wired as well as wireless devices that incorporate the potential of millions, and soon billions, of embedded devices enabling new forms of computation and service delivery. Service providers such as broadband cable operators continue to contribute towards this expansion with growing Cloud system infrastructures combined with deployments of increasingly powerful embedded devices across broadband networks. Broadband networks enable access to service provider Cloud data-centers and the Internet from numerous devices. These include home computers, smart-phones, tablets, game-consoles, sensor-networks, and set-top box devices. With these trends in mind, I propose the concept of broadband embedded computing as the utilization of a broadband network of embedded devices for collective computation in conjunction with centralized Cloud infrastructures. I claim that this form of distributed computing results in a new class of heterogeneous Cloud systems, service delivery and application enablement. To support these claims, I present a collection of research contributions in adapting distributed software platforms that include MPI and MapReduce to support simultaneous application execution across centralized data-center blade servers and resource-constrained embedded devices. Leveraging these contributions, I develop two complete prototype system implementations to demonstrate an architecture for heterogeneous Cloud systems based on broadband embedded computing. Each system is validated by executing experiments with applications taken from bioinformatics and image processing as well as communication and computational benchmarks. This vision, however, is not without challenges. The questions on how to adapt standard distributed computing paradigms such as MPI and MapReduce for implementation on potentially resource-constrained embedded devices, and how to adapt cluster computing runtime environments to enable heterogeneous process execution across millions of devices remain open-ended. This dissertation presents methods to begin addressing these open-ended questions through the development and testing of both experimental broadband embedded computing systems and in-depth characterization of broadband network behavior. I present experimental results and comparative analysis that offer potential solutions for optimal scalability and performance for constructing broadband embedded computing systems. I also present a number of contributions enabling practical implementation of both heterogeneous Cloud systems and novel application services based on broadband embedded computing

Designing Human-Centered Collective Intelligence

Human-Centered Collective Intelligence (HCCI) is an emergent research area that seeks to bring together major research areas like machine learning, statistical modeling, information retrieval, market research, and software engineering to address challenges pertaining to deriving intelligent insights and solutions through the collaboration of several intelligent sensors, devices and data sources. An archetypal contextual CI scenario might be concerned with deriving affect-driven intelligence through multimodal emotion detection sources in a bid to determine the likability of one movie trailer over another. On the other hand, the key tenets to designing robust and evolutionary software and infrastructure architecture models to address cross-cutting quality concerns is of keen interest in the “Cloud” age of today. Some of the key quality concerns of interest in CI scenarios span the gamut of security and privacy, scalability, performance, fault-tolerance, and reliability. I present recent advances in CI system design with a focus on highlighting optimal solutions for the aforementioned cross-cutting concerns. I also describe a number of design challenges and a framework that I have determined to be critical to designing CI systems. With inspiration from machine learning, computational advertising, ubiquitous computing, and sociable robotics, this literature incorporates theories and concepts from various viewpoints to empower the collective intelligence engine, ZOEI, to discover affective state and emotional intent across multiple mediums. The discerned affective state is used in recommender systems among others to support content personalization. I dive into the design of optimal architectures that allow humans and intelligent systems to work collectively to solve complex problems. I present an evaluation of various studies that leverage the ZOEI framework to design collective intelligence

Improved planning and resource management in next generation green mobile communication networks

In upcoming years, mobile communication networks will experience a disruptive reinventing process through the deployment of post 5th Generation (5G) mobile networks. Profound impacts are expected on network planning processes, maintenance and operations, on mobile services, subscribers with major changes in their data consumption and generation behaviours, as well as on devices itself, with a myriad of different equipment communicating over such networks. Post 5G will be characterized by a profound transformation of several aspects: processes, technology, economic, social, but also environmental aspects, with energy efficiency and carbon neutrality playing an important role. It will represent a network of networks: where different types of access networks will coexist, an increasing diversity of devices of different nature, massive cloud computing utilization and subscribers with unprecedented data-consuming behaviours. All at greater throughput and quality of service, as unseen in previous generations. The present research work uses 5G new radio (NR) latest release as baseline for developing the research activities, with future networks post 5G NR in focus. Two approaches were followed: i) method re-engineering, to propose new mechanisms and overcome existing or predictably existing limitations and ii) concept design and innovation, to propose and present innovative methods or mechanisms to enhance and improve the design, planning, operation, maintenance and optimization of 5G networks. Four main research areas were addressed, focusing on optimization and enhancement of 5G NR future networks, the usage of edge virtualized functions, subscriber’s behavior towards the generation of data and a carbon sequestering model aiming to achieve carbon neutrality. Several contributions have been made and demonstrated, either through models of methodologies that will, on each of the research areas, provide significant improvements and enhancements from the planning phase to the operational phase, always focusing on optimizing resource management. All the contributions are retro compatible with 5G NR and can also be applied to what starts being foreseen as future mobile networks. From the subscriber’s perspective and the ultimate goal of providing the best quality of experience possible, still considering the mobile network operator’s (MNO) perspective, the different proposed or developed approaches resulted in optimization methods for the numerous problems identified throughout the work. Overall, all of such contributed individually but aggregately as a whole to improve and enhance globally future mobile networks. Therefore, an answer to the main question was provided: how to further optimize a next-generation network - developed with optimization in mind - making it even more efficient while, simultaneously, becoming neutral concerning carbon emissions. The developed model for MNOs which aimed to achieve carbon neutrality through CO2 sequestration together with the subscriber’s behaviour model - topics still not deeply focused nowadays – are two of the main contributions of this thesis and of utmost importance for post-5G networks.Nos próximos anos espera-se que as redes de comunicações móveis se reinventem para lá da 5ª Geração (5G), com impactos profundos ao nível da forma como são planeadas, mantidas e operacionalizadas, ao nível do comportamento dos subscritores de serviços móveis, e através de uma miríade de dispositivos a comunicar através das mesmas. Estas redes serão profundamente transformadoras em termos tecnológicos, económicos, sociais, mas também ambientais, sendo a eficiência energética e a neutralidade carbónica aspetos que sofrem uma profunda melhoria. Paradoxalmente, numa rede em que coexistirão diferentes tipos de redes de acesso, mais dispositivos, utilização massiva de sistema de computação em nuvem, e subscritores com comportamentos de consumo de serviços inéditos nas gerações anteriores. O trabalho desenvolvido utiliza como base a release mais recente das redes 5G NR (New Radio), sendo o principal focus as redes pós-5G. Foi adotada uma abordagem de "reengenharia de métodos” (com o objetivo de propor mecanismos para resolver limitações existentes ou previsíveis) e de “inovação e design de conceitos”, em que são apresentadas técnicas e metodologias inovadoras, com o principal objetivo de contribuir para um desenho e operação otimizadas desta geração de redes celulares. Quatro grandes áreas de investigação foram endereçadas, contribuindo individualmente para um todo: melhorias e otimização generalizada de redes pós-5G, a utilização de virtualização de funções de rede, a análise comportamental dos subscritores no respeitante à geração e consumo de tráfego e finalmente, um modelo de sequestro de carbono com o objetivo de compensar as emissões produzidas por esse tipo de redes que se prevê ser massiva, almejando atingir a neutralidade carbónica. Como resultado deste trabalho, foram feitas e demonstradas várias contribuições, através de modelos ou metodologias, representando em cada área de investigação melhorias e otimizações, que, todas contribuindo para o mesmo objetivo, tiveram em consideração a retro compatibilidade e aplicabilidade ao que se prevê que sejam as futuras redes pós 5G. Focando sempre na perspetiva do subscritor da melhor experiência possível, mas também no lado do operador de serviço móvel – que pretende otimizar as suas redes, reduzir custos e maximizar o nível de qualidade de serviço prestado - as diferentes abordagens que foram desenvolvidas ou propostas, tiveram como resultado a resolução ou otimização dos diferentes problemas identificados, contribuindo de forma agregada para a melhoria do sistema no seu todo, respondendo à questão principal de como otimizar ainda mais uma rede desenvolvida para ser extremamente eficiente, tornando-a, simultaneamente, neutra em termos de emissões de carbono. Das principais contribuições deste trabalho relevam-se precisamente o modelo de compensação das emissões de CO2, com vista à neutralidade carbónica e um modelo de análise comportamental dos subscritores, dois temas ainda pouco explorados e extremamente importantes em contexto de redes futuras pós-5G

An Approach to Guide Users Towards Less Revealing Internet Browsers

When browsing the Internet, HTTP headers enable both clients and servers send extra data in their requests or responses such as the User-Agent string. This string contains information related to the sender’s device, browser, and operating system. Previous research has shown that there are numerous privacy and security risks result from exposing sensitive information in the User-Agent string. For example, it enables device and browser fingerprinting and user tracking and identification. Our large analysis of thousands of User-Agent strings shows that browsers differ tremendously in the amount of information they include in their User-Agent strings. As such, our work aims at guiding users towards using less exposing browsers. In doing so, we propose to assign an exposure score to browsers based on the information they expose and vulnerability records. Thus, our contribution in this work is as follows: first, provide a full implementation that is ready to be deployed and used by users. Second, conduct a user study to identify the effectiveness and limitations of our proposed approach. Our implementation is based on using more than 52 thousand unique browsers. Our performance and validation analysis show that our solution is accurate and efficient. The source code and data set are publicly available and the solution has been deployed

Achieving Digital Wellbeing Through Digital Self-Control Tools: A Systematic Review and Meta-Analysis

Public media and researchers in different areas have recently focused on perhaps unexpected problems that derive from an excessive and frequent use of technology, giving rise to a new kind of psychological "digital" wellbeing. Such a novel and pressing topic has fostered, both in the academia and in the industry, the emergence of a variety of digital self-control tools allowing users to self-regulate their technology use through interventions like timers and lock-out mechanisms. While these emerging technologies for behavior change hold great promise to support people's digital wellbeing, we still have a limited understanding of their real effectiveness, as well as of how to best design and evaluate them. Aiming to guide future research in this important domain, this article presents a systematic review and a meta-analysis of current work on tools for digital self-control. We surface motivations, strategies, design choices, and challenges that characterize the design, development, and evaluation of digital self-control tools. Furthermore, we estimate their overall effect size on reducing (unwanted) technology use through a meta-analysis. By discussing our findings, we provide insights on how to (i) overcome a limited perspective that exclusively focuses on technology overuse and self-monitoring tools, (ii) evaluate digital self-control tools through long-term studies and standardized measures, and (iii) bring ethics in the digital wellbeing discourse and deal with the business model of contemporary tech companies