A smartphone agent for QoE evaluation and user classification over mobile networks

The continuous growth of mobile users and bandwidth-consuming applications and the shortage of radio resources put a serious challenge on how to efficiently exploit existing networks and contemporary improve Quality of Experience. One of the most relevant problem for network operators is thus to find an explicit relationship between QoS and QoE, for the purpose of maximizing the latter while saving precious resources. In order to accomplish this challenging task, we present TeleAbarth, an innovative Android application entirely developed at TelecomItalia Laboratories, able to contemporary collect network measurements and end-users quality feedback regarding the use of smartphone applications. We deployed TeleAbarth in a field experimentation in order to study the relationship between QoS and QoE for video streaming applications, in terms of downstream bandwidth and video loading time. On the basis of the results obtained, we propose a technique to classify user behavior through his or her reliability, sensibility and fairness

Microphone smart device fingerprinting from video recordings

This report aims at summarizing the on-going research activity carried out by DG-JRC in the framework of the institutional project Authors and Victims Identification of Child Abuse on-line, concerning the use of microphone fingerprinting for source device classification. Starting from an exhaustive study of the State of Art regarding the matter, this report describes a feasibility study about the adoption of microphone fingerprinting for source identification of video recordings. A set of operational scenarios have been established in collaboration with EUROPOL law enforcers, according to investigators needs. A critical analysis of the obtained results has demonstrated the feasibility of microphone fingerprinting and it has suggested a set of recommendations, both in terms of usability and future researches in the field.JRC.E.3-Cyber and Digital Citizens' Securit

Typical Phone Use Habits: Intense Use Does Not Predict Negative Well-Being

Not all smartphone owners use their device in the same way. In this work, we uncover broad, latent patterns of mobile phone use behavior. We conducted a study where, via a dedicated logging app, we collected daily mobile phone activity data from a sample of 340 participants for a period of four weeks. Through an unsupervised learning approach and a methodologically rigorous analysis, we reveal five generic phone use profiles which describe at least 10% of the participants each: limited use, business use, power use, and personality- & externally induced problematic use. We provide evidence that intense mobile phone use alone does not predict negative well-being. Instead, our approach automatically revealed two groups with tendencies for lower well-being, which are characterized by nightly phone use sessions.Comment: 10 pages, 6 figures, conference pape

CommuniSense: Crowdsourcing Road Hazards in Nairobi

Nairobi is one of the fastest growing metropolitan cities and a major business and technology powerhouse in Africa. However, Nairobi currently lacks monitoring technologies to obtain reliable data on traffic and road infrastructure conditions. In this paper, we investigate the use of mobile crowdsourcing as means to gather and document Nairobi's road quality information. We first present the key findings of a city-wide road quality survey about the perception of existing road quality conditions in Nairobi. Based on the survey's findings, we then developed a mobile crowdsourcing application, called CommuniSense, to collect road quality data. The application serves as a tool for users to locate, describe, and photograph road hazards. We tested our application through a two-week field study amongst 30 participants to document various forms of road hazards from different areas in Nairobi. To verify the authenticity of user-contributed reports from our field study, we proposed to use online crowdsourcing using Amazon's Mechanical Turk (MTurk) to verify whether submitted reports indeed depict road hazards. We found 92% of user-submitted reports to match the MTurkers judgements. While our prototype was designed and tested on a specific city, our methodology is applicable to other developing cities.Comment: In Proceedings of 17th International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI 2015

A Concept for a Trustworthy Integration of Smartphones in Business Environments

Smartphones are commonly used within business environments nowadays. They provide sophisticated communicational means which go far beyond simple telephone capabilities. Email access and particular apps on the device are examples of their versatile abilities. While these features allow them to be used in a very flexible way, e.g. in different infrastructures, they impose new threats to their surrounding infrastructure. For example, if used in an environment which allows the installation of custom apps, malicious software may be placed on the device. In order to mitigate these threats, a detailed awareness combined with the possibility to enforce certain constraints on such devices need to be established. In detail, it is necessary to include such devices into a decision making process which decides about the policy compliance of such devices. The policy used in this process defines the rules which apply to the particular infrastructure, e.g. if custom apps are allowed or if a specific software version may not be allowed. However, even when relying on this process, there is one limitation as it does not include a trust-based evaluation. This leads to the problem that a malicious smartphone might compromise the information used for the decision making process which should determine the policy compliance of this device. This renders the overall approach ineffective as the decision wether a device is policy compliant or not may be false. Given that, the thesis presented here provides means to evaluate the trustworthiness of such information to allow a trustworthy decision making about the policy compliance. It therefore introduces two things: (1) a generic trust model for such environments and (2) a domain-specific extension called Trustworthy Context-related Signature and Anomaly Detection system for Smartphones (TCADS). The trust model (1) allows to specify, to calculate and to evaluate trust for the information used by the decision making process. More in detail, the trust founding process of (1) is done by introducing so-called security properties which allow to rate the trustworthiness of certain aspects. The trust model does not limit these aspects to a particular type. That is, device-specific aspects like the number of installed apps or the current version of the operating system may be used as well as device independent aspects like communicational parameters. The security properties defined in (1) are then used to calculate an overall trust level, which provides an evaluable representation of trust for the information used by the decision making process. The domain-specific extension (2) uses the trust model and provides a deployable trust-aware decision making solution for smartphone environments. The resulting system, TCADS, allows not only to consider trust within the decisions about the policy compliance but also enables to base the decisions solely on the trust itself. Besides the theoretical specification of the trust model (1) and the domain-specific extension (2), a proof of concept implementation is given. This implementation leverages both, the abilities of the generic trust model (1) as well as the abilities of the TCADS system (2), thus providing a deployable set of programs. Using this proof of concept implementation, an assessment shows the benefits of the proposed concept and its practical relevance. A conclusion and an outlook to future work extending this approach is given at the end of this thesis.Smartphones sind in heutigen Unternehmensnetzen mittlerweile nicht mehr wegzudenken. Über einfache Telefonie-basierte Fähigkeiten hinaus bieten sie Eigenschaften wie zum Beispiel Email-Zugriff oder hohe Anpassbarkeit auf Basis von Apps. Obwohl diese Funktionalitäten eine vielseitige Nutzung solcher Smartphones erlauben, stellen sie gleichzeitig eine neuartige Bedrohung für die umgebende Infrastruktur dar. Erlaubt eine spezifische Umgebung beispielsweise die Installation von eigenen Apps auf dem Smartphone, so ist es über diesen Weg möglich, Schadprogramme auf dem Gerät zu platzieren. Um diesen Bedrohungen entgegenzuwirken, ist es zum einen nötig Smartphones in der jeweiligen Umgebung zu erkennen und zum anderen, Richtlinien auf den jeweiligen Geräten durchsetzen zu können. Die durchzusetzenden Richtlinien legen fest, welche Einschränkungen für die jeweilige Umgebung gelten, z.B. die Erlaubnis zur Installation von eigenen Apps oder die Benutzung einer bestimmten Softwareversion. Aber auch wenn eine entsprechende Lösung zur Einbeziehung von Smartphones in die Infrastruktur verwendet wird, bleibt ein Problem ungelöst: die Betrachtung der Vertrauenswürdigkeit von durch das Smartphone bereitgestellten Informationen. Diese Einschränkung führt zu dem Problem, dass ein entsprechend kompromittiertes Smartphone die Informationen, welche zur Entscheidungsfindung über die Richtlinienkonformität des Gerätes verwendet werden, in einer Art und Weise ändert, welche den gesamten Entscheidungsprozess ineffizient und somit wirkungslos macht. Die hier vorliegende Arbeit stellt daher einen neuen Ansatz vor um einen vertrauenswürdigen Entscheidungsprozess zur Regelkonformität des Gerätes zu ermöglichen. Im Detail werden dazu zwei Ansätze vorgestellt: (1) Ein generisches Modell für Vertrauensürdigkeit sowie eine (2) domänenspezifische Abbildung dieses Modells, welches als Trustworthy Context-related Signature and Anomaly Detection system for Smartphones (TCADS) bezeichnet wird. Das Modell für Vertrauenswürdigkeit (1) erlaubt die Definition, Berechnung und Auswertung von Vetrauenswürdigkeit für Informationen welche im Entscheidungsprozess verwendet werden. Im Detail basiert die Vertrauenswürdigkeitsbestimmung auf Grundfaktoren für Vertrauen, den sogenannten Sicherheitseigenschaften. Diese Eigenschaften bewerten die Vertrauenswürdigkeit anhand von bestimmten Aspekten die entweder gerätespezifisch und Geräteunabhängig sein können. Basierend auf dieser Bewertung wird dann eine Gesamtvertrauenswürdigkeit, der sogenannte Trust Level berechnet. Dieser Trust Level erlaubt die Berücksichtigung der Vertrauenswürdigkeit bei der Entscheidungsfindung. Teil (2) der Lösung stellt, basierend auf dem Modell der Vertrauenswürdigkeit, ein System zur vertrauensbasierten Entscheidungsfindung in Smartphone Umgebungen bereit. Mit diesem System, TCADS, ist es nicht nur möglich, Entscheidungen auf ihre Korrektheit bezüglich der Vertrauenswürdigkeit zu prüfen, sondern auch Entscheidungen komplett auf Basis der Vertrauenswürdigkeit zu fällen. Neben dem allgemeingültigen Modell (1) und dem daraus resultierenden domänenspezifischen System (2), stellt die Arbeit außerdem einen Tragfähigkeitsnachweis in Form einer Referenzimplementierung bereit. Diese Implementierung nutzt sowohl Fähigkeiten des Modells der Vertrauenswürdigkeit (1) als auch des TCADS Systems (2) und stellt ein nutzbares Set von Programmen bereit. Eine Evaluierung basierend auf diesem Tragfähigkeitsnachweis zeigt die Vorteile und die Praktikabilität der vorgestellten Ansätze. Abschließend findet sich eine Zusammenfassung der Arbeit sowie ein Ausblick auf weiterführende Fragestellungen