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.

Reuse of software components orientated to iOS mobile devices

Within the next few pages, I will try to give a wide description of the project that I have been doing for IK4-Ikerlan. For the last six months, I have been working in developing a socket-based application for Apple devices. These devices work under the iOS operative system, which is programmed in Objective-C, a language similar to C. Although I did not have the chance to develop this application for Apple TV, I was able to create an application for iPhone and another one for iPad. The only difference between both applications was the screen resolution, but we decided to make them separately, as it would be really hard to combine both resolutions, and wallpapers, everything in the same workspace. Finally, it is necessary to add that the main goal was not to create a new application for iOS, but to translate an Android application into iOS. To achieve this, it is required to translate Java code into Objective- C, which is the language used to develop applications for all kinds of Apple devices. Fortunately, there is a tool created by Google, which helped us with this exercise. This tool is called j2ObjC, and it is still being developed.

Desarrollo de cliente OMA PoC para Android

[ES]Se presenta el siguiente proyecto de desarrollo, enfocado en el contexto de suplir las necesidades de los equipos de emergencias. Actualmente los equipos de emergencias, hacen uso de walkie talkies para comunicarse entre sí, es decir, hacen uso de la tecnología PTT (Push-to-talk). Es una comunicación unidireccional de un usuario a muchos, de manera que pueden transmitir la información necesaria a varios usuarios simultáneamente. Por otra parte, la comunicación mediante esta tecnología hace posible que sea en tiempo real sin prácticamente ningún retraso. Sin embargo el uso de esta forma de comunicación trae consigo algunos inconvenientes. Por ejemplo, los dispositivos tienen un rango de alcance de transmisión-recepción limitado. Además la banda de frecuencia para poder comunicarse debe ser reservada a fin de evitar posibles problemas de comunicación debido a que el canal estuviera ocupado por otros usuarios, posibles interferencias, etc. La reserva de este rango de frecuencia, supone un coste añadido para el uso de esta tecnología. Con el desarrollo de las redes móviles que ofrecen grandes velocidades de transmisión, se hace posible el uso de la tecnología PTT mediante la red móvil existente. De esta manera, surge el siguiente proyecto de desarrollo de una aplicación móvil Android, como cliente que haga uso de la tecnología PTT sobre la red móvil PoC (Push-to-talk Over Cellular).

Evaluation of Setup Procedures on Mobile Devices Based on Users’ Initial Experience

Users’ initial perceptions of their competence are key motivational factors for further use. However, initial tasks on a mobile operating system (OS) require setup procedures, which are currently largely inconsistent, do not provide users with clear, visible and immediate feedback on their actions, and require significant adjustment time for first-time users. This paper reports on a study with ten users, carried out to better understand how both prior experience and initial interaction with two touchscreen mobile interfaces (Apple iOS and Google Android) affected setup task performance and motivation. The results show that the reactions to setup on mobile interfaces appear to be partially dependent on which device was experienced first. Initial experience with lower-complexity devices improves performance on higher-complexity devices, but not vice versa. Based on these results, the paper proposes six guidelines for designers to design more intuitive and motivating user interfaces (UI) for setup procedures. The preliminary results indicate that these guidelines can contribute to the design of more inclusive mobile platforms and further work to validate these findings is proposed.

Conservative Interventions for mobile Pes Planus in Adults: a systematic review

Antecedentes. Pes Adulto planus (pie plano) es un problema común encontrado por muchos profesionales de la salud. A pesar de la percepción de que el pie plano puede causar dolor y deteriorar su función, la disponibilidad y el uso generalizado de diversos tratamientos, no hay consenso sobre la estrategia óptima de tratamiento. Objetivo. Evaluar la efectividad de las intervenciones conservadoras (no quirúrgicos) para pie plano en los adultos. Método. Se realizó una búsqueda sistemática de la literatura. Esto incluye: el Registro Cochrane Central de Ensayos Controlados; los Juicios CMSG Especializados Registro; una búsqueda electrónica se realizó utilizando MEDLINE (1960 a junio de 2012), EMBASE (1980 a junio de 2012), y CINAHL (1982 - junio de 2012). Revistas especializadas, listas de referencias de ensayos y artículos de revisión se realizaron búsquedas manuales. Criterios de selección: Ensayos aleatorios o cuasialeatorios de intervenciones de tratamiento para el pie plano en los adultos. Se excluyeron los ensayos que incluyeron patologías específicas como el dolor plantar del talón, las fracturas por sobrecarga de los metatarsianos, disfunción del tendón tibial posterior-, fracturas de tobillo, patologías del pie reumatoide, enfermedades neuromusculares y las complicaciones del pie diabético. Recopilación y análisis de datos: Dos autores seleccionaron de forma independiente los resultados de la búsqueda para identificar a aquellos que satisfacen los criterios de inclusión y evaluaron la calidad de los incluidos mediante una lista de control basado en la Evaluación de la Colaboración Cochrane de Riesgo. Esta herramienta se centró en el riesgo de la selección, el rendimiento, la detección, la heterogeneidad y el sesgo de notificación. Resultados. Cuatro ensayos, con 140 sujetos, cumplieron los criterios de inclusión para la revisión. Los cuatro fueron juzgados como de alto riesgo de sesgo en al menos un área, y también estaban en riesgo de sesgo incierto en al menos otra zona. Todos anotaron altamente en relación al sesgo de deserción, debido al corto seguimiento tiempos y diseños experimentales utilizados. Los datos no se agruparon debido al alto nivel de heterogeneidad identificada en las intervenciones evaluadas, los participantes seleccionados y medir los resultados. Los resultados de un estudio sugieren que después de cuatro semanas de uso ortesis puede resultar en una mejora significativa en vaivén lateral medio, y pueden resultar en una mejor, aunque no significativa, en general relacionados con la calidad de vida de los pies (Roma 2004). Un estudio (Redmond 2009) sugiere que su efecto sobre la distribución de la presión plantar en el pie puede no depender de si son personalizados o dispositivos prefabricados. Aunque este estudio se identificaron cambios significativos en algunas variables de presión plantar tanto con la costumbre y dispositivos prefabricados, otro (Esterman 2005) no encontró ningún efecto significativo de longitud ¾ ortesis prefabricadas sobre el dolor, la incidencia de lesiones, salud pie o de calidad de vida en un grupo de reclutas de la fuerza aérea. El cuarto estudio (Jung 2009) sugiere que el ejercicio de los músculos intrínsecos del pie puede mejorar el efecto de las ortesis. A pesar de estos resultados, ya que cada estudio incurrió riesgo de sesgo en al menos un área no se pueden sacar conclusiones

Analysis of Bayesian classification-based approaches for Android malware detection

Mobile malware has been growing in scale and complexity spurred by the unabated uptake of smartphones worldwide. Android is fast becoming the most popular mobile platform resulting in sharp increase in malware targeting the platform. Additionally, Android malware is evolving rapidly to evade detection by traditional signature-based scanning. Despite current detection measures in place, timely discovery of new malware is still a critical issue. This calls for novel approaches to mitigate the growing threat of zero-day Android malware. Hence, the authors develop and analyse proactive machine-learning approaches based on Bayesian classification aimed at uncovering unknown Android malware via static analysis. The study, which is based on a large malware sample set of majority of the existing families, demonstrates detection capabilities with high accuracy. Empirical results and comparative analysis are presented offering useful insight towards development of effective static-analytic Bayesian classification-based solutions for detecting unknown Android malware.

Android Malware Detection Using Parallel Machine Learning Classifiers

Mobile malware has continued to grow at an alarming rate despite on-going mitigation efforts. This has been much more prevalent on Android due to being an open platform that is rapidly overtaking other competing platforms in the mobile smart devices market. Recently, a new generation of Android malware families has emerged with advanced evasion capabilities which make them much more difficult to detect using conventional methods. This paper proposes and investigates a parallel machine learning based classification approach for early detection of Android malware. Using real malware samples and benign applications, a composite classification model is developed from parallel combination of heterogeneous classifiers. The empirical evaluation of the model under different combination schemes demonstrates its efficacy and potential to improve detection accuracy. More importantly, by utilizing several classifiers with diverse characteristics, their strengths can be harnessed not only for enhanced Android malware detection but also quicker white box analysis by means of the more interpretable constituent classifiers.

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 Malware Detection: an Eigenspace Analysis Approach

The battle to mitigate Android malware has become more critical with the emergence of new strains incorporating increasingly sophisticated evasion techniques, in turn necessitating more advanced detection capabilities. Hence, in this paper we propose and evaluate a machine learning based approach based on eigenspace analysis for Android malware detection using features derived from static analysis characterization of Android applications. Empirical evaluation with a dataset of real malware and benign samples show that detection rate of over 96% with a very low false positive rate is achievable using the proposed method.

Event-driven implicit authentication for mobile access control

In order to protect user privacy on mobile devices, an event-driven implicit authentication scheme is proposed in this paper. Several methods of utilizing the scheme for recognizing legitimate user behavior are investigated. The investigated methods compute an aggregate score and a threshold in real-time to determine the trust level of the current user using real data derived from user interaction with the device. The proposed scheme is designed to: operate completely in the background, require minimal training period, enable high user recognition rate for implicit authentication, and prompt detection of abnormal activity that can be used to trigger explicitly authenticated access control. In this paper, we investigate threshold computation through standard deviation and EWMA (exponentially weighted moving average) based algorithms. The result of extensive experiments on user data collected over a period of several weeks from an Android phone indicates that our proposed approach is feasible and effective for lightweight real-time implicit authentication on mobile smartphones.

Android as a cloud ticket validator

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

Simulação de plataformas para dispositivos móveis: infraestrutura de simulação sensorial para android

Projeto para obtenção do grau de Mestre em Engenharia Informática e de Computadores

Handling mobility on a QoS-Aware servicebased framework for mobile systems

Mobile applications are becoming increasingly more complex and making heavier demands on local system resources. Moreover, mobile systems are nowadays more open, allowing users to add more and more applications, including third-party developed ones. In this perspective, it is increasingly expected that users will want to execute in their devices applications which supersede currently available resources. It is therefore important to provide frameworks which allow applications to benefit from resources available on other nodes, capable of migrating some or all of its services to other nodes, depending on the user needs. These requirements are even more stringent when users want to execute Quality of Service (QoS) aware applications, such as voice or video. The required resources to guarantee the QoS levels demanded by an application can vary with time, and consequently, applications should be able to reconfigure themselves. This paper proposes a QoS-aware service-based framework able to support distributed, migration-capable, QoS-enabled applications on top of the Android Operating system.

Educational application of remote experimentation for mobile devices

In this article the authors describe the application development RExMobile and the importance of remote experimentation via mobile devices, especially smartphones simple, beyond the space provided for this application in education. The article deals the creation, software and hardware that provide an interactive and dynamic way to attract more students to use these experiments remote, serving as support to teachers to science teaching from its initial series. The ease and availability of smartphones, even these students of basic education, permits the reach of new users and in different places. Thus, the practice of remote experimentation in mobile devices enables new spaces for access and interaction. Are used for developing software free or low cost, HTML5 and jQuery Mobile framework, that enable the creation of pages compatible with different mobile operating systems such as iOS, Android, Windows Phone, some Symbian, among others. Also are demonstrated patterns layouts that allow greater accessibility.