Managing big data experiments on smartphones

The explosive number of smartphones with ever growing sensing and computing capabilities have brought a paradigm shift to many traditional domains of the computing field. Re-programming smartphones and instrumenting them for application testing and data gathering at scale is currently a tedious and time-consuming process that poses significant logistical challenges. Next generation smartphone applications are expected to be much larger-scale and complex, demanding that these undergo evaluation and testing under different real-world datasets, devices and conditions. In this paper, we present an architecture for managing such large-scale data management experiments on real smartphones. We particularly present the building blocks of our architecture that encompassed smartphone sensor data collected by the crowd and organized in our big data repository. The given datasets can then be replayed on our testbed comprising of real and simulated smartphones accessible to developers through a web-based interface. We present the applicability of our architecture through a case study that involves the evaluation of individual components that are part of a complex indoor positioning system for smartphones, coined Anyplace, which we have developed over the years. The given study shows how our architecture allows us to derive novel insights into the performance of our algorithms and applications, by simplifying the management of large-scale data on smartphones

Automating Software Development for Mobile Computing Platforms

Mobile devices such as smartphones and tablets have become ubiquitous in today\u27s computing landscape. These devices have ushered in entirely new populations of users, and mobile operating systems are now outpacing more traditional desktop systems in terms of market share. The applications that run on these mobile devices (often referred to as apps ) have become a primary means of computing for millions of users and, as such, have garnered immense developer interest. These apps allow for unique, personal software experiences through touch-based UIs and a complex assortment of sensors. However, designing and implementing high quality mobile apps can be a difficult process. This is primarily due to challenges unique to mobile development including change-prone APIs and platform fragmentation, just to name a few. in this dissertation we develop techniques that aid developers in overcoming these challenges by automating and improving current software design and testing practices for mobile apps. More specifically, we first introduce a technique, called Gvt, that improves the quality of graphical user interfaces (GUIs) for mobile apps by automatically detecting instances where a GUI was not implemented to its intended specifications. Gvt does this by constructing hierarchal models of mobile GUIs from metadata associated with both graphical mock-ups (i.e., created by designers using photo-editing software) and running instances of the GUI from the corresponding implementation. Second, we develop an approach that completely automates prototyping of GUIs for mobile apps. This approach, called ReDraw, is able to transform an image of a mobile app GUI into runnable code by detecting discrete GUI-components using computer vision techniques, classifying these components into proper functional categories (e.g., button, dropdown menu) using a Convolutional Neural Network (CNN), and assembling these components into realistic code. Finally, we design a novel approach for automated testing of mobile apps, called CrashScope, that explores a given android app using systematic input generation with the intrinsic goal of triggering crashes. The GUI-based input generation engine is driven by a combination of static and dynamic analyses that create a model of an app\u27s GUI and targets common, empirically derived root causes of crashes in android apps. We illustrate that the techniques presented in this dissertation represent significant advancements in mobile development processes through a series of empirical investigations, user studies, and industrial case studies that demonstrate the effectiveness of these approaches and the benefit they provide developers

On the adoption of end-user IT security measures

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A methodology for the design of application-specific cyber-physical social sensing co-simulators

Cyber-Physical Social Sensing (CPSS) is a new trend in the context of pervasive sensing. In these new systems, various domains coexist in time, evolve together and influence each other. Thus, application-specific tools are necessary for specifying and validating designs and simulating systems. However, nowadays, different tools are employed to simulate each domain independently. Mainly, the cause of the lack of co-simulation instruments to simulate all domains together is the extreme difficulty of combining and synchronizing various tools. In order to reduce that difficulty, an adequate architecture for the final co-simulator must be selected. Therefore, in this paper the authors investigate and propose a methodology for the design of CPSS co-simulation tools. The paper describes the four steps that software architects should follow in order to design the most adequate co-simulator for a certain application, considering the final users’ needs and requirements and various additional factors such as the development team’s experience. Moreover, the first practical use case of the proposed methodology is provided. An experimental validation is also included in order to evaluate the performing of the proposed co-simulator and to determine the correctness of the proposal

Usable privacy and security in smart homes

Ubiquitous computing devices increasingly dominate our everyday lives, including our most private places: our homes. Homes that are equipped with interconnected, context-aware computing devices, are considered “smart” homes. To provide their functionality and features, these devices are typically equipped with sensors and, thus, are capable of collecting, storing, and processing sensitive user data, such as presence in the home. At the same time, these devices are prone to novel threats, making our homes vulnerable by opening them for attackers from outside, but also from within the home. For instance, remote attackers who digitally gain access to presence data can plan for physical burglary. Attackers who are physically present with access to devices could access associated (sensitive) user data and exploit it for further cyberattacks. As such, users’ privacy and security are at risk in their homes. Even worse, many users are unaware of this and/or have limited means to take action. This raises the need to think about usable mechanisms that can support users in protecting their smart home setups. The design of such mechanisms, however, is challenging due to the variety and heterogeneity of devices available on the consumer market and the complex interplay of user roles within this context. This thesis contributes to usable privacy and security research in the context of smart homes by a) understanding users’ privacy perceptions and requirements for usable mechanisms and b) investigating concepts and prototypes for privacy and security mechanisms. Hereby, the focus is on two specific target groups, that are inhabitants and guests of smart homes. In particular, this thesis targets their awareness of potential privacy and security risks, enables them to take control over their personal privacy and security, and illustrates considerations for usable authentication mechanisms. This thesis provides valuable insights to help researchers and practitioners in designing and evaluating privacy and security mechanisms for future smart devices and homes, particularly targeting awareness, control, and authentication, as well as various roles.Computer und andere „intelligente“, vernetzte Geräte sind allgegenwärtig und machen auch vor unserem privatesten Zufluchtsort keinen Halt: unserem Zuhause. Ein „intelligentes Heim“ verspricht viele Vorteile und nützliche Funktionen. Um diese zu erfüllen, sind die Geräte mit diversen Sensoren ausgestattet – sie können also in unserem Zuhause sensitive Daten sammeln, speichern und verarbeiten (bspw. Anwesenheit). Gleichzeitig sind die Geräte anfällig für (neuartige) Cyberangriffe, gefährden somit unser Zuhause und öffnen es für potenzielle – interne sowie externe – Angreifer. Beispielsweise könnten Angreifer, die digital Zugriff auf sensitive Daten wie Präsenz erhalten, einen physischen Überfall in Abwesenheit der Hausbewohner planen. Angreifer, die physischen Zugriff auf ein Gerät erhalten, könnten auf assoziierte Daten und Accounts zugreifen und diese für weitere Cyberangriffe ausnutzen. Damit werden die Privatsphäre und Sicherheit der Nutzenden in deren eigenem Zuhause gefährdet. Erschwerend kommt hinzu, dass viele Nutzenden sich dessen nicht bewusst sind und/oder nur limitierte Möglichkeiten haben, effiziente Gegenmaßnahmen zu ergreifen. Dies macht es unabdingbar, über benutzbare Mechanismen nachzudenken, die Nutzende beim Schutz ihres intelligenten Zuhauses unterstützen. Die Umsetzung solcher Mechanismen ist allerdings eine große Herausforderung. Das liegt unter anderem an der großen Vielfalt erhältlicher Geräte von verschiedensten Herstellern, was das Finden einer einheitlichen Lösung erschwert. Darüber hinaus interagieren im Heimkontext meist mehrere Nutzende in verschieden Rollen (bspw. Bewohner und Gäste), was die Gestaltung von Mechanismen zusätzlich erschwert. Diese Doktorarbeit trägt dazu bei, benutzbare Privatsphäre- und Sicherheitsmechanismen im Kontext des „intelligenten Zuhauses“ zu entwickeln. Insbesondere werden a) die Wahrnehmung von Privatsphäre sowie Anforderungen an potenzielle Mechanismen untersucht, sowie b) Konzepte und Prototypen für Privatsphäre- und Sicherheitsmechanismen vorgestellt. Der Fokus liegt hierbei auf zwei Zielgruppen, den Bewohnern sowie den Gästen eines intelligenten Zuhauses. Insbesondere werden in dieser Arbeit deren Bewusstsein für potenzielle Privatsphäre- und Sicherheits-Risiken adressiert, ihnen Kontrolle über ihre persönliche Privatsphäre und Sicherheit ermöglicht, sowie Möglichkeiten für benutzbare Authentifizierungsmechanismen für beide Zielgruppen aufgezeigt. Die Ergebnisse dieser Doktorarbeit legen den Grundstein für zukünftige Entwicklung und Evaluierung von benutzbaren Privatsphäre und Sicherheitsmechanismen im intelligenten Zuhause

Managing Smartphone Testbeds with SmartLab

The explosive number of smartphones with ever growing sensing and computing capabilities have brought a paradigm shift to many traditional domains of the computing field. Re-programming smartphones and instrumenting them for application testing and data gathering at scale is currently a tedious and time-consuming process that poses significant logistical challenges. In this paper, we make three major contributions: First, we propose a comprehensive architecture, coined SmartLab1, for managing a cluster of both real and virtual smartphones that are either wired to a private cloud or connected over a wireless link. Second, we propose and describe a number of Android management optimizations (e.g., command pipelining, screen-capturing, file management), which can be useful to the community for building similar functionality into their systems. Third, we conduct extensive experiments and microbenchmarks to support our design choices providing qualitative evidence on the expected performance of each module comprising our architecture. This paper also overviews experiences of using SmartLab in a research-oriented setting and also ongoing and future development efforts

Enhancing Social Media Platforms for Educational and Humanitarian Knowledge Sharing:Analytics, Privacy, Discovery, and Delivery Aspects

Social media (SM) platforms have demonstrated their ability to facilitate knowledge sharing on the global scale. They are increasingly often employed in educational and humanitarian domains where, despite their general benefits, they expose challenges peculiar to these domains. Specifically, the research context of this thesis is directed by my participation in the Go-Lab European project and my collaboration with Médecins Sans Frontières (MSF) where SM platforms were used extensively. In this thesis, we address four challenges regarding analytics, privacy, discovery, and delivery, aiming to answer corresponding four research questions. How to provide user-oriented analytics in knowledge sharing systems to support awareness and reflection? What privacy management interfaces and mechanisms are suitable for knowledge analytics and learning analytics? How to enable discovery of knowledge relevant to user interests? How to facilitate knowledge delivery into settings where Internet connectivity is limited or absent? Henceforward, we provide an overview of our results. Analytics. To enable awareness and reflection for an SM platform users, we propose the embedded contextual analytics model where the analytics is embedded into the interaction context and presents information relevant to that particular context. Also, we propose two general architectures materializing this model respectfully based on real-time analytical applications and a scalable analytic back-end. Using these architectures, we provided analytics services to the SM platform users. We conducted an evaluation with the users demonstrating that embedded contextual analytics was useful to support their awareness and reflection. Privacy. To address the privacy concerns associated with the recording, storage, and analysis of user interaction traces, we propose a novel agent-based privacy management model. Our proposal uses a metaphor of physical presence of a tracking agent in an interaction context making the platform user aware of the tracking and allows to manage the tracking policy in a way similar to the physical world. We have implemented the proposed privacy interface in an SM platform and obtained positive evaluation results with the users. Discovery. Due to a large number of content items stored in SM platforms, it can be challenging for the users to find relevant knowledge. Addressing this challenge, we propose an interactive recommender system based on user interests enabling discovery of relevant content and people. We have implemented the proposed recommender in an SM platform and conducted two evaluations with platform users. The evaluations demonstrated the ability of the approach to identify relevant user interests and to recommend relevant content. Delivery. At the moment of writing in 2016, near half of the world's population still does not have reliable Internet access. Often, the places where humanitarian action is needed have limited Internet connection. We propose a novel knowledge delivery model that relies on a peer-to-peer middleware and uses low-cost computers for local knowledge replication. We have developed a system implementing the model and evaluated it during eight deployments in MSF missions. The evaluation demonstrated its knowledge delivery abilities and its usefulness for the field staff

Human-in-the-Loop Cyber-Physical-Systems based on Smartphones

Tese de doutoramento em Ciências e Tecnologias da Informação, apresentada ao Departamento de Engenharia Informática da Faculdade de Ciências e Tecnologia da Universidade de CoimbraTechnological devices increasingly become smaller, more mobile, powerful and efficient. However, each time we have to hurdle through unintuitive menus, errors and incompatibilities we become stressed by our technology. As first put forward by the renowned computer scientist Mark Weiser, the ultimate form of computers may be an extension of our subconscious. The ideal computer would be capable of truly understanding people's unconscious actions and desires. Instead of humans adapting to technology and learning how to use it, it would be technology that would adapt to the disposition and uniqueness of each human being. This thesis focuses on the realm of Human-in-the-loop Cyber-Physical Systems (HiTLCPSs). HiTLCPSs infer the users’ intents, psychological states, emotions and actions, using this information to determine the system's behavior. This involves using a large variety of sensors and mobile devices to monitor and evaluate human nature. Therefore, this technology has strong ties with wireless sensor networks, robotics, machine-learning and the Internet of Things. In particular, our work focuses on the usage of smartphones within these systems. It begins by describing a framework to understand the principles and theory of HiTLCPSs. It provides some insights into current research being done on this topic, its challenges, and requirements. Another of the thesis' objectives is to present our innovative taxonomy of human roles, where we attempt to understand how a human may interact with HiTLCPSs and how to best explore this resource. This thesis also describes concrete examples of the practical usage of HiTL paradigms. As such, we included a comprehensive description of our research work and associated prototypes, where the major theoretical concepts behind HiTLCPS were applied and evaluated to specific scenarios. Finally, we discuss our personal view on the future and evolution of these systems.A tecnologia tem vindo a tornar-se cada vez mais pequena, móvel, poderosa e eficiente. No entanto, lidar com menus pouco intuitivos, erros, e incompatibilidades, causa frustração aos seus utilizadores. Segundo o reconhecido cientista Mark Weiser, os computadores do futuro poderão vir a existir como se fossem uma extensão do nosso subconsciente. O computador ideal seria capaz de entender, em toda a sua plenitude, as ações e os desejos inconscientes dos seres humanos. Em vez de serem os humanos a adaptarem-se à tecnologia e a aprender a usá-la, seria a tecnologia a aprender a adaptar-se à disposição e individualidade de cada ser humano. Esta tese foca-se na área dos Human-in-the-loop Cyber-Physical Systems (HiTLCPSs). Os HiTLCPSs inferem as intenções, estados psicológicos, emoções e ações dos seus utilizadores, usando esta informação para determinar o comportamento do sistema ciber-físico. Isto envolve a utilização de uma grande variedade de sensores e dispositivos móveis que monitorizam e avaliam a natureza humana. Assim sendo, esta tecnologia tem fortes ligações com redes de sensores sem fios, robótica, algoritmos de aprendizagem de máquina e a Internet das Coisas. Em particular, o nosso trabalho focou-se na utilização de smartphones dentro destes sistemas. Começamos por descrever uma estrutura para compreender os princípios e teoria associados aos HiTLCPSs. Esta análise permitiu-nos adquirir alguma clareza sobre a investigação a ser feita sobre este tópico, e sobre os seus desafios e requisitos. Outro dos objetivos desta tese é o de apresentar a nossa inovadora taxonomia sobre os papeis do ser humano nos HiTLCPSs, onde tentamos perceber as possíveis interações do ser humano com estes sistemas e as melhores formas de explorar este recurso. Esta tese também descreve exemplos concretos da utilização prática dos paradigmas HiTL. Desta forma, incluímos uma descrição do nosso trabalho experimental e dos protótipos que lhe estão associados, onde os conceitos teóricos dos HiTLCPSs foram aplicados e avaliados em diversos casos de estudo. Por fim, apresentamos a nossa perspetiva pessoal sobre o futuro e evolução destes sistemas.Fundação Luso-Americana para o DesenvolvimentoFP7-ICT-2007-2 GINSENG projectiCIS project (CENTRO-07-ST24-FEDER-002003)SOCIALITE project (PTDC/EEI-SCR/2072/2014