Prototipo di schermo adattativo basato su Android e Bluetooth Low Energy

La tesi nasce da un'attività di ricerca approfondita su alcune tecnologie innovative e all'avanguardia nell'ambito del mobile computing e dell'Internet of Things. Tra queste il focus principale è orientato allo studio del Bluetooth Low Energy, nuova specifica di Bluetooth caratterizzata principalmente da un consumo di energia assai ridotto. In particolare, si è approfondito il suo funzionamento nel caso dei beacon, piccoli dispositivi che permettono una localizzazione mediante l'invio di un segnale BLE. Inoltre è stata analizzata la possibilità di interazione con Android, poiché oggigiorno non si può evitare di pensare a come queste tecnologie possano interfacciarsi con il mondo degli smartphone e dei tablet. Come conseguenza di tale attività di ricerca è stato analizzato un caso di studio che permettesse di applicare le tecnologie studiate e la loro interazione. Si è pensato quindi a un piccolo sistema distribuito per schermi adattativi (capaci di modificare i contenuti visualizzati in relazione ad eventi esterni) affinché ogni schermo mostrasse dinamicamente l'orario delle lezioni di ciascuno studente all'avvicinarsi di quest'ultimo, e solo per il tempo di permanenza nei pressi dello schermo. Si è quindi progettato e sviluppato un prototipo, e infine durante il testing si sono potute verificare le attuali potenzialità di queste tecnologie e trarre conclusioni sulla possibilità della loro futura diffusione e di impiego in contesti differenti.

Android en el Hogar Digital usando UPnP y Redes LonWorks

Este Proyecto Final de Carrera se centra principalmente en el estudio de las tecnologías aplicadas al Hogar Digital (HD) y así poder desarrollar nuevas herramientas aplicadas a este Sector. La primera tecnología estudiada es LonWorks que se escogió porque en la EUITT se cuenta con un entorno domótico donde se aplica esta tecnología, materializado como una maqueta de una instalación LonWorks en un HD. Sobre este entorno se ha desarrollado una nueva forma de gestionar y controlar los elementos de una Red LonWorks mediante la tecnología Universal Plug & Play (UPnP). Los dispositivos LonWorks han sido recubiertos con una capa con la que se consigue tratar los elementos LonWorks como dispositivos UPnP, pudiendo de esta manera trabajar bajo un mismo formato de dispositivo. Este formato está definido por un documento denominado Descripción del Dispositivo UPnP. Por tanto, no es necesario conocer el estado de los dispositivos de la Red LonWorks, sino únicamente trabajar bajo una Red UPnP, creando nuevos dispositivos UPnP, puntos de Control y servicios a partir de los elementos LonWorks. Una vez realizado el recubrimiento del sistema LonWorks con UPnP, se ha definido y desarrollado una aplicación para Android que, permite controlar los elementos de la maqueta del HD desde un Smartphone o una Tablet. El acceso a la Red LonWorks de la maqueta del HD se hace a través de la interfaz Web Services SOAP/XML del dispositivo iLON100. ABSTRACT. This Final Degree Project is mainly focused on the study of the technologies applied to Digital Home and thus be able to develop new tools applied to this area. The first study is LonWorks technology which was chosen because the EUITT has a domotic environment where this technology is applied, materialized as a demonstrator of a LonWorks installation in HD. With this environment has developed a new way to manage and control the elements of a LonWorks network through technology by Universal Plug & Play (UPnP). LonWorks devices are covered with a layer and it is achieved LonWorks elements treat as UPnP devices. In this way the LonWorks elements can work under one device format. This format is defined by a document called UPnP Device Description. Therefore, it isn't necessary to know the state of the LonWorks network devices, but only work under an UPnP network, creating new UPnP devices, control points and services from LonWorks elements. After backfill of LonWorks system with UPnP, have being defined and developed an Android application that allow controlling the elements of the mockup of HD from Smartphone or a Tablet. The LonWorks network Access of the mockup of HD is done through the Web Interface Services SOAP / XML iLON100 device.

Enhancing security of linux-based android devices

Our daily lives become more and more dependent upon smartphones due to their increased capabilities. Smartphones are used in various ways from payment systems to assisting the lives of elderly or disabled people. Security threats for these devices become increasingly dangerous since there is still a lack of proper security tools for protection. Android emerges as an open smartphone platform which allows modification even on operating system level. Therefore, third-party developers have the opportunity to develop kernel-based low-level security tools which is not normal for smartphone platforms. Android quickly gained its popularity among smartphone developers and even beyond since it bases on Java on top of "open" Linux in comparison to former proprietary platforms which have very restrictive SDKs and corresponding APIs. Symbian OS for example, holding the greatest market share among all smartphone OSs, was closing critical APIs to common developers and introduced application certification. This was done since this OS was the main target for smartphone malwares in the past. In fact, more than 290 malwares designed for Symbian OS appeared from July 2004 to July 2008. Android, in turn, promises to be completely open source. Together with the Linux-based smartphone OS OpenMoko, open smartphone platforms may attract malware writers for creating malicious applications endangering the critical smartphone applications and owners� privacy. In this work, we present our current results in analyzing the security of Android smartphones with a focus on its Linux side. Our results are not limited to Android, they are also applicable to Linux-based smartphones such as OpenMoko Neo FreeRunner. Our contribution in this work is three-fold. First, we analyze android framework and the Linux-kernel to check security functionalities. We survey wellaccepted security mechanisms and tools which can increase device security. We provide descriptions on how to adopt these security tools on Android kernel, and provide their overhead analysis in terms of resource usage. As open smartphones are released and may increase their market share similar to Symbian, they may attract attention of malware writers. Therefore, our second contribution focuses on malware detection techniques at the kernel level. We test applicability of existing signature and intrusion detection methods in Android environment. We focus on monitoring events on the kernel; that is, identifying critical kernel, log file, file system and network activity events, and devising efficient mechanisms to monitor them in a resource limited environment. Our third contribution involves initial results of our malware detection mechanism basing on static function call analysis. We identified approximately 105 Executable and Linking Format (ELF) executables installed to the Linux side of Android. We perform a statistical analysis on the function calls used by these applications. The results of the analysis can be compared to newly installed applications for detecting significant differences. Additionally, certain function calls indicate malicious activity. Therefore, we present a simple decision tree for deciding the suspiciousness of the corresponding application. Our results present a first step towards detecting malicious applications on Android-based devices.

Static analysis of executables for collaborative malware detection on Android

Smartphones are getting increasingly popular and several malwares appeared targeting these devices. General countermeasures to smartphone malwares are currently limited to signature-based antivirus scanners which efficiently detect known malwares, but they have serious shortcomings with new and unknown malwares creating a window of opportunity for attackers. As smartphones become host for sensitive data and applications, extended malware detection mechanisms are necessary complying with the corresponding resource constraints. The contribution of this paper is twofold. First, we perform static analysis on the executables to extract their function calls in Android environment using the command readelf. Function call lists are compared with malware executables for classifying them with PART, Prism and Nearest Neighbor Algorithms. Second, we present a collaborative malware detection approach to extend these results. Corresponding simulation results are presented.

An Android application sandbox system for suspicious software detection

Smartphones are steadily gaining popularity, creating new application areas as their capabilities increase in terms of computational power, sensors and communication. Emerging new features of mobile devices give opportunity to new threats. Android is one of the newer operating systems targeting smartphones. While being based on a Linux kernel, Android has unique properties and specific limitations due to its mobile nature. This makes it harder to detect and react upon malware attacks if using conventional techniques. In this paper, we propose an Android Application Sandbox (AASandbox) which is able to perform both static and dynamic analysis on Android programs to automatically detect suspicious applications. Static analysis scans the software for malicious patterns without installing it. Dynamic analysis executes the application in a fully isolated environment, i.e. sandbox, which intervenes and logs low-level interactions with the system for further analysis. Both the sandbox and the detection algorithms can be deployed in the cloud, providing a fast and distributed detection of suspicious software in a mobile software store akin to Google's Android Market. Additionally, AASandbox might be used to improve the efficiency of classical anti-virus applications available for the Android operating system.

Developing and benchmarking native Linux applications on Android

Smartphones get increasingly popular where more and more smartphone platforms emerge. Special attention was gained by the open source platform Android which was presented by the Open Handset Alliance (OHA) hosting members like Google, Motorola, and HTC. Android uses a Linux kernel and a stripped-down userland with a custom Java VM set on top. The resulting system joins the advantages of both environments, while third-parties are intended to develop only Java applications at the moment. In this work, we present the benefit of using native applications in Android. Android includes a fully functional Linux, and using it for heavy computational tasks when developing applications can bring in substantional performance increase. We present how to develop native applications and software components, as well as how to let Linux applications and components communicate with Java programs. Additionally, we present performance measurements of native and Java applications executing identical tasks. The results show that native C applications can be up to 30 times as fast as an identical algorithm running in Dalvik VM. Java applications can become a speed-up of up to 10 times if utilizing JNI.

Monitoring android for collaborative anomaly detection : a first architectural draft

Our daily lives become more and more dependent upon smartphones due to their increased capabilities. Smartphones are used in various ways, e.g. for payment systems or assisting the lives of elderly or disabled people. Security threats for these devices become more and more dangerous since there is still a lack of proper security tools for protection. Android emerges as an open smartphone platform which allows modification even on operating system level and where third-party developers first time have the opportunity to develop kernel-based low-level security tools. Android quickly gained its popularity among smartphone developers and even beyond since it bases on Java on top of "open" Linux in comparison to former proprietary platforms which have very restrictive SDKs and corresponding APIs. Symbian OS, holding the greatest market share among all smartphone OSs, was even closing critical APIs to common developers and introduced application certification. This was done since this OS was the main target for smartphone malwares in the past. In fact, more than 290 malwares designed for Symbian OS appeared from July 2004 to July 2008. Android, in turn, promises to be completely open source. Together with the Linux-based smartphone OS OpenMoko, open smartphone platforms may attract malware writers for creating malicious applications endangering the critical smartphone applications and owners privacy. Since signature-based approaches mainly detect known malwares, anomaly-based approaches can be a valuable addition to these systems. They base on mathematical algorithms processing data that describe the state of a certain device. For gaining this data, a monitoring client is needed that has to extract usable information (features) from the monitored system. Our approach follows a dual system for analyzing these features. On the one hand, functionality for on-device light-weight detection is provided. But since most algorithms are resource exhaustive, remote feature analysis is provided on the other hand. Having this dual system enables event-based detection that can react to the current detection need. In our ongoing research we aim to investigates the feasibility of light-weight on-device detection for certain occasions. On other occasions, whenever significant changes are detected on the device, the system can trigger remote detection with heavy-weight algorithms for better detection results. In the absence of the server respectively as a supplementary approach, we also consider a collaborative scenario. Here, mobile devices sharing a common objective are enabled by a collaboration module to share information, such as intrusion detection data and results. This is based on an ad-hoc network mode that can be provided by a WiFi or Bluetooth adapter nearly every smartphone possesses.

Google Android : a comprehensive introduction

Google Android, Google's new product and its first attempt to enter the mobile market, might have an equal impact on mobile users like Apple's hyped product, the iPhone. In this Technical report we are going to present the Google Android platform, what Android is, describe why it might be considered as a worthy rival to Apple's iPhone. We will describe parts of its internals, take a look "under the hood" while explaining components of the underlying operating system. We will show how to develop applications for this platform, which difficulties a developer might have to face, and how developers can possibly use other programming languages to develop for Android than the propagated language Java.

Urkiolaenea: Sistemas multidispositivo para negocios tradicionales

“Urkiolaenea: Sistemas multidispositivo para negocios tradicionales” es un proyecto realizado en la empresa OrekaI.T. dentro de un contexto formativo, ya que a su vez es el proyecto con el que finalizo mis estudios de Ingeniería Informática. Con él, se ha pretendido dar respuesta a las necesidades de un cliente real que dispone de un negocio tradicional.En este caso, Urkiolaenea, una negocio de alojamiento rural que requería de una imagen renovada en Internet para lograr ser más competitiva en el ámbito del turismo rural, además de un sistema de gestión para mejorar sus procesos de negocio. Por otra parte, con este proyecto no sólo se ha buscado cumplir con las expectativas del cliente sino ir más allá, buscando las soluciones más adecuadas ante el mercado actual en Internet, dominado por los dispositivos móviles inteligentes. Por ello, gran parte de los esfuerzos realizados en este proyecto se han enfocado en conseguir que Urkiolaenea sea accesible cómodamente por cualquier persona, independientemente del dispositivo desde el que acceda.

A New Android Malware Detection Method Using Bayesian Classification

Mobile malware has been growing in scale and complexity as smartphone usage continues to rise. Android has surpassed other mobile platforms as the most popular whilst also witnessing a dramatic increase in malware targeting the platform. A worrying trend that is emerging is the increasing sophistication of Android malware to evade detection by traditional signature-based scanners. As such, Android app marketplaces remain at risk of hosting malicious apps that could evade detection before being downloaded by unsuspecting users. Hence, in this paper we present an effective approach to alleviate this problem based on Bayesian classification models obtained from static code analysis. The models are built from a collection of code and app characteristics that provide indicators of potential malicious activities. The models are evaluated with real malware samples in the wild and results of experiments are presented to demonstrate the effectiveness of the proposed approach.

High accuracy android malware detection using ensemble learning

With over 50 billion downloads and more than 1.3 million apps in Google’s official market, Android has continued to gain popularity amongst smartphone users worldwide. At the same time there has been a rise in malware targeting the platform, with more recent strains employing highly sophisticated detection avoidance techniques. As traditional signature based methods become less potent in detecting unknown malware, alternatives are needed for timely zero-day discovery. Thus this paper proposes an approach that utilizes ensemble learning for Android malware detection. It combines advantages of static analysis with the efficiency and performance of ensemble machine learning to improve Android malware detection accuracy. The machine learning models are built using a large repository of malware samples and benign apps from a leading antivirus vendor. Experimental results and analysis presented shows that the proposed method which uses a large feature space to leverage the power of ensemble learning is capable of 97.3 % to 99% detection accuracy with very low false positive rates.

Android as a cloud ticket validator

Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Informática e de Computadores

Classificação de atividades físicas através do uso do acelerómetro do smartphone

Dissertação de natureza científica realizada para a obtenção do grau de Mestre em Engenharia de redes de comunicação e Multimédia

En utvärdering av Android och Iphone : För utveckling av webbtjänstunderstödda applikationer ämnade för intern distribution

Tack vare bättre och bättre förutsättningar för utveckling av mobila applikationer, samt utbredning av internetbaserade tjänster, presenteras här ett underlag inför val av mobil utvecklingsplattform. De undersökta plattformarna är Android och Iphone på grund av deras växande utbredning på smartphonemarknaden. Studien presenterar förutsättningar för att utveckla webbtjänst-understödda applikationer för intern distribuering. Ett visuellt tilltalande användargränssnitt är också i fokus för den typen av applikation studien riktar sig mot.Vi har kommit fram till att Android är lättare att lära sig om man kommer ifrån en Java- eller .Netmiljö samt lättare att distribuera. Iphone har däremot bättre stöd för att utveckla grafiskt tilltalande applikationer. Båda plattformarna har dock bristfälligt stöd för kommunikation via webbtjänster. Detta resultat uppnåddes genom litteraturstudier, samt en fallstudie där vi utvecklade applikationer med fokus på just webbtjänstkommunikation, intern distribuering samt ett tilltalande användargränssnitt.

Design de interfaces para aplicativo de smartphone como recurso auxiliar no acompanhamento clínico de pacientes fibromiálgicos

Este trabalho tem como objetivo o desenvolvimento de interfaces com o usuário para aplicativo móvel smartphones com intuito de contribuir para a eficiência das atividades de profissionais e pesquisadores da área de fisioterapia ao oferecer suporte ao acompanhamento clínico da dor no tratamento de pacientes fibromiálgicos. Utilizando a abordagem de Design Centrado no Usuário - DCU, foram realizadas entrevistas e uma investigação contextual para a identificação inicial dos problemas e necessidades dos usuários. Verificou-se que as atividades de monitoramento e acompanhamento das sessões do tratamento de pacientes fibromiálgicos são, tradicionalmente, realizadas por meio de manipulando de formulários e fichas em papel (registro das condições de saúde do paciente) e escalas de classificação da dor em formato impresso (apresentadas ao paciente para indicação de sua dor percebida para cada ponto pré-determinado do corpo). Os procedimentos envolvidos nestas atividades dificultam o gerenciamento do desempenho do tratamento, o que, segundo relatos, reflete no comprometimento dos pacientes na adesão e frequência as sessões. A partir da observação e do levantamento das necessidades desses profissionais diante de suas atividades, foi proposto um aplicativo para smartphone com a intenção de minimizar os problemas ocasionados pelo uso das ferramentas convencionais e de prover informações rápidas acerca dos dados coletados. Então, seguindo a abordagem do DCU foi elaborado um modelo conceitual durante a etapa de concepção de soluções, o qual guiou a criação dos protótipos. A avaliação das interfaces do protótipo foi realizada com o envolvimento dos usuários a partir da técnica de avaliação cooperativa. Seus resultados proporcionaram o refinamento das interfaces e o desenvolvimento de uma nova proposta do design das interfaces em protótipo de alta fidelidade, produzido para o ambiente Android. Assim, esse trabalho faz parte do processo de desenvolvimento de um produto de software personalizado com foco na concepção e avaliação das interfaces com o usuário. Por meio da metodologia aplicada, observaram-se indícios os quais sugerem que as interfaces propostas apresentaram-se como um recurso facilitador e capaz de contribuir para eficiência das atividades no acompanhamento do tratamento de pacientes fibromiálgicos