856 resultados para TuCSoN, Android, Porting


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Communication and coordination are two key-aspects in open distributed agent system, being both responsible for the system’s behaviour integrity. An infrastructure capable to handling these issues, like TuCSoN, should to be able to exploit modern technologies and tools provided by fast software engineering contexts. Thesis aims to demonstrate TuCSoN infrastructure’s abilities to cope new possibilities, hardware and software, offered by mobile technology. The scenarios are going to configure, are related to the distributed nature of multi-agent systems where an agent should be located and runned just on a mobile device. We deal new mobile technology frontiers concerned with smartphones using Android operating system by Google. Analysis and deployment of a distributed agent-based system so described go first to impact with quality and quantity considerations about available resources. Engineering issue at the base of our research is to use TuCSoN against to reduced memory and computing capability of a smartphone, without the loss of functionality, efficiency and integrity for the infrastructure. Thesis work is organized on two fronts simultaneously: the former is the rationalization process of the available hardware and software resources, the latter, totally orthogonal, is the adaptation and optimization process about TuCSoN architecture for an ad-hoc client side release.

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Il campo della coordinazione può beneficiare di nuovi strumenti e tecnologie per il proprio sviluppo o per rendere accessibili le sue funzionalità ad un pubblico più vasto. Il progetto TuCSoN, in particolare, include lo strumento Inspector tramite il quale è possibile monitorare ed interagire con l'intero spazio di coordinazione. Al fine di rendere disponibili queste funzionalità anche al mondo mobile è necessario eseguire il porting dell'applicazione. In questa tesi, perciò, verranno prima di tutto analizzate le caratteristiche principali dei modelli di coordinazione e, in particolare, del modello TuCSoN. In seguito eseguiremo un'introduzione sulla tecnologia Android, che ci fornirà gli strumenti necessari per la creazione di un framework mobile equivalente all'Inspector. Infine verranno affrontate le problematiche principali per eseguire con successo il porting, come ad esempio la necessità di ridefinire l'intera interfaccia grafica o l'utilizzo di nuovi componenti quali i service e le activity. Questa operazione, quindi, dimostrerà l'esigenza di adattare l'Inspector ai meccanismi appartenenti al nuovo ambiente di esecuzione.

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TuCSoN (Tuple Centres Spread over the Network) è un modello di coordinazione per processi distribuiti o agenti autonomi. Il modello di TuCSoN viene implementato come un middleware distribuito Java-based, distribuito Open Source sotto la licenza LGPL tramite Googlecode. Il fatto che lo stesso sia Open Source e Java-based ha reso possibile il suo porting su Android, rendendo il noto sistema operativo di Google un possibile agente partecipante ad un sistema TuCSoN. La tesi descrive il percorso che ha portato dallo studio dell'infrastruttura TuCSoN e del sistema Android alla realizzazione dell'applicazione Android, rendendo possibile a qualsiasi dispositivo Android di partecipare ad un sistema TuCSoN. Nel particolare l'obiettivo finale dell'applicazione Android, e di questa tesi, è rendere lo smartphone un nodo TuCSoN funzionante. La tesi non si pone l'obiettivo di analizzare ed esplorare le funzionalità e le possibilitàa delle due tecnologie principali trattate (Android e TuCSoN) nel loro singolo, quanto quello di esplorare le criticità che un porting di questo tipo comporta, quali ad esempio le differenze intrinseche fra la JVM e la DalvikVM e come aggirarle, o le funzionalità di Android e come utilizzarle allo scopo di realizzare un applicazione che funga da server ad una infra- struttura distribuita, oppure le differenze a livello di gestione della GUI fra Android e plain-java, e di analizzare le soluzioni trovate per risolvere (o dove non era possibile risolvere evitare) tali problemi al fine del raggiungimento dell'obiettivo che ci si era prefissati.

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Il lavoro svolto in questa tesi consiste nell'effettuare il porting del Monitor di rete da Linux ad Android,facente parte di un sistema più complesso conosciuto come ABPS. Il ruolo del monitor è quello di configurare dinamicamente tutte le interfacce di rete disponibili sul dispositivo sul quale lavora,in modo da essere connessi sempre alla miglior rete conosciuta,ad esempio al miglior Access Point nel caso del interfaccia wireless.

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Tesi riguardante il porting della macchina virtuale UmView sul sistema operativo Android ARM. Tratta sia di aspetti relativi a umview sia del porting in generale quale del debug remoto con gdb.

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La tesi si concentra sull’infrastruttura di coordinazione TuCSoN on Android, realizzando il refactoring del servizio di geolocalizzazione platform-independent (lato infrastruttura) e platform-dependent (lato mobile device), nonché l’integrazione del modello event-driven con la proprietà di situatedness.

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Lo scopo della tesi è quello di definire un modello di astrazione di coordinazione space-aware nell'ottica dei dispositivi mobili e del pervasive computing, concentrandosi in particolare sul modello TuCSoN e sui tuple centre ReSpecT.

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Si continua il lavoro riguardo il porting di UMView su android studiando i problemi affrontati nelle tesi precedenti e suggerendo soluzioni per superarli. Sono stati effettuati anche esperimenti sulla nuova runtime di Android, ART, per studiare casi di possibili incompatibilità ed eventuali differenze di gestione rispetto a Dalvik.

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La tesi analizza lo stack di comunicazione Bluetooth e le possibili estensioni di TuCSoN per permettere il suo utilizzo. Come risultato di questo lavoro, sono state realizzate delle librerie software che permettono lo scambio di messaggi tra TuCSoN su Android e dispositivi Bluetooth.

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At least two important transportation planning activities rely on planning-level crash prediction models. One is motivated by the Transportation Equity Act for the 21st Century, which requires departments of transportation and metropolitan planning organizations to consider safety explicitly in the transportation planning process. The second could arise from a need for state agencies to establish incentive programs to reduce injuries and save lives. Both applications require a forecast of safety for a future period. Planning-level crash prediction models for the Tucson, Arizona, metropolitan region are presented to demonstrate the feasibility of such models. Data were separated into fatal, injury, and property-damage crashes. To accommodate overdispersion in the data, negative binomial regression models were applied. To accommodate the simultaneity of fatality and injury crash outcomes, simultaneous estimation of the models was conducted. All models produce crash forecasts at the traffic analysis zone level. Statistically significant (p-values < 0.05) and theoretically meaningful variables for the fatal crash model included population density, persons 17 years old or younger as a percentage of the total population, and intersection density. Significant variables for the injury and property-damage crash models were population density, number of employees, intersections density, percentage of miles of principal arterial, percentage of miles of minor arterials, and percentage of miles of urban collectors. Among several conclusions it is suggested that planning-level safety models are feasible and may play a role in future planning activities. However, caution must be exercised with such models.

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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.

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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.

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Smartphones started being targets for malware in June 2004 while malware count increased steadily until the introduction of a mandatory application signing mechanism for Symbian OS in 2006. From this point on, only few news could be read on this topic. Even despite of new emerging smartphone platforms, e.g. android and iPhone, malware writers seemed to lose interest in writing malware for smartphones giving users an unappropriate feeling of safety. In this paper, we revisit smartphone malware evolution for completing the appearance list until end of 2008. For contributing to smartphone malware research, we continue this list by adding descriptions on possible techniques for creating the first malware(s) for Android platform. Our approach involves usage of undocumented Android functions enabling us to execute native Linux application even on retail Android devices. This can be exploited to create malicious Linux applications and daemons using various methods to attack a device. In this manner, we also show that it is possible to bypass the Android permission system by using native Linux applications.

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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.