Adoption of smart mobile devices (smartphones, wearables, etc.) is rapidly growing. There are already over 2 billion smartphone users worldwide [1] and the percentage of smartphone users is expected to be over 50% in the next five years [2]. These devices feature rich sensing capabilities which allow inferences about mobile device user’s surroundings and behavior. Multiple and diverse sensors common on such mobile devices facilitate observing the environment from different perspectives, which helps to increase robustness of inferences and enables more complex context detection tasks. Though a larger number of sensing modalities can be beneficial for more accurate and wider mobile context detection, integrating these sensor streams is non-trivial. This thesis presents how multimodal sensor data can be integrated to facilitate ro- bust and energy efficient mobile context detection, considering three important and challenging detection tasks: indoor localization, indoor-outdoor detection and human activity recognition. This thesis presents three methods for multimodal sensor inte- gration, each applied for a different type of context detection task considered in this thesis. These are gradually decreasing in design complexity, starting with a solution based on an engineering approach decomposing context detection to simpler tasks and integrating these with a particle filter for indoor localization. This is followed by man- ual extraction of features from different sensors and using an adaptive machine learn- ing technique called semi-supervised learning for indoor-outdoor detection. Finally, a method using deep neural networks capable of extracting non-intuitive features di- rectly from raw sensor data is used for human activity recognition; this method also provides higher degree of generalization to other context detection tasks. Energy efficiency is an important consideration in general for battery powered mo- bile devices and context detection is no exception. In the various context detection tasks and solutions presented in this thesis, particular attention is paid to this issue by relying largely on sensors that consume low energy and on lightweight computations. Overall, the solutions presented improve on the state of the art in terms of accuracy and robustness while keeping the energy consumption low, making them practical for use on mobile devices.

It is commonly acknowledged that mobile devices now form an integral part of an individual’s everyday life. The modern mobile handheld devices are capable to provide a wide range of services and applications over multiple networks. With the increasing capability and accessibility, they introduce additional demands in term of security. This thesis explores the need for authentication on mobile devices and proposes a novel mechanism to improve the current techniques. The research begins with an intensive review of mobile technologies and the current security challenges that mobile devices experience to illustrate the imperative of authentication on mobile devices. The research then highlights the existing authentication mechanism and a wide range of weakness. To this end, biometric approaches are identified as an appropriate solution an opportunity for security to be maintained beyond point-of-entry. Indeed, by utilising behaviour biometric techniques, the authentication mechanism can be performed in a continuous and transparent fashion. This research investigated three behavioural biometric techniques based on SMS texting activities and messages, looking to apply these techniques as a multi-modal biometric authentication method for mobile devices. The results showed that linguistic profiling; keystroke dynamics and behaviour profiling can be used to discriminate users with overall Equal Error Rates (EER) 12.8%, 20.8% and 9.2% respectively. By using a combination of biometrics, the results showed clearly that the classification performance is better than using single biometric technique achieving EER 3.3%. Based on these findings, a novel architecture of multi-modal biometric authentication on mobile devices is proposed. The framework is able to provide a robust, continuous and transparent authentication in standalone and server-client modes regardless of mobile hardware configuration. The framework is able to continuously maintain the security status of the devices. With a high level of security status, users are permitted to access sensitive services and data. On the other hand, with the low level of security, users are required to re-authenticate before accessing sensitive service or data.

With the continued proliferation of mobile devices, the collection of information associated with such devices and their users - such as location, installed applications and cookies associated with built-in browsers - has become increasingly straightforward. By analysing such information, organisations are often able to deliver more relevant and better focused advertisements. Although such Targeted Mobile Advertising (TMA) offers great benefits to advertisers, it gives rise to a number of concerns, with privacy-related concerns being prominent amongst them. It follows that there is a need for an advertisement-selection mechanism that can support the existing TMA business model in a manner that takes into account consumers' privacy concerns. The research described in this dissertation explores the delicate balance between the goals of the advertisers and the consumers: advertisers pursue profits by applying TMA, which violates consumers' privacy; consumers hope to benefit from useful mobile advertisements without compromising their personal information. The conflicts of interests between consumers and advertisers in the context of targeted mobile advertising brings us to our research question: Is it possible to develop a privacy-preserving TMA framework that enables mobile users to take advantage of useful advertising services without their privacy being compromised, and without impacting significantly advertising effectiveness? In order to answer this question, this dissertation presents four main contributions. First, we report upon the result of a qualitative study to discuss the balance that needs to be struck between privacy and utility in this emerging area. Second, a number of formal models are developed to reason about privacy, as well as to reason about the relationship between privacy and utility in the context of TMA. Third, a novel ad-selection architecture, PPTMA (Privacy-Preserving Targeted Mobile Advertising), is presented and evaluated. Finally, a privacy-preserving advertisement-selection mechanism, AdSelector, is introduced. The mechanism is novel in its combination of a user subscription mechanism, a two-stage ad-selection process, and the application of a trustworthy billing system.

A Denial of Service (DoS) attack is an incident in which the user is deprived of the services of a resource he is expected to have. With the increasing reliance on mobile devices like laptops and palmtops, a new type of DoS attack is possible that attacks the batteries of these devices, called "sleep deprivation attacks". The goal of sleep deprivation attacks is to rapidly drain the battery of the mobile devices, rendering the device inoperable long before the expected battery lifetime, thus denying the service the user expects from the mobile device. The purpose of this research is to investigate these types of attacks so that proper defense mechanisms can be put in place before the attacks become a more sophisticated and potent force. This research presents three different possible methods that can be adopted by an attacker to drain the battery of a device i.e. malignant attacks, benign attacks and network service request attacks. These attacks are implemented on a variety of mobile computing platforms like palmtops and a laptop and the corresponding results are presented. Finally, a mathematical model is presented that estimates the battery life of a device based on its power consumption in various power management states and expected usage. This model can also be used to predict the impact of a DoS attack on the battery life of the device under attack. / Master of Science

The recent advances in mobile computing devices and wireless networking produced the technical platform for multimedia services over thin mobile devices. Nowadays, we are witnessing an important growth in applications using thin mobile devices, such as social networks, virtual walkthrough, media streaming, and augmented reality (AR), just to mention a few. Most of these applications are based on the client-server architecture, however several studies showed that the client-server architecture suffers from various issues, such as the server bottleneck, latency and the lack of scalability. This led most of the systems to switch to the peer-to-peer (P2P)-like environment for its scalability and potential cost saving. P2P multimedia streaming over thin mobile devices-based classes of applications has known a significant growth during the last years. Although P2P video streaming over thin mobile devices received a great deal of attention, the application of 3D streaming over mobile devices was challenging mainly due to the limited mobile resources and capabilities, as well as the wireless medium limitations. Having 3D streaming over Mobile Ad hoc Networks (MANET) is considered more challenging given that the 3D streaming-based system has to deal with a dynamic environment resulting from nodes mobility, which may lead to route breakages and connection loss. Therefore, one of the major difficulties in 3D streaming over MANET is related to the supplying partner's strategy that aims at determining the most suitable source holding the required 3D data to stream it quickly and efficiently to the requesters. In this thesis, we propose our P2P based 3D streaming system which we refer to as MOSAIC as well as a suite of supplying partner strategy protocols for P2P 3D streaming over thin mobile devices. Our proposed suite of protocols selects the potential sources that have the relevant 3D data, based on a set of criteria such as the source location, the mobile device's available resources as well as its residual energy. We also proposed a multihop supplying partner selection protocol that takes into account the signal strength and the nodes mobility when streaming the relevant 3D data. The performance evaluation obtained to evaluate our MOSAIC system as well as our suite of protocols using an extensive set of NS2 simulation experiments, is then reported.

To keep up in the rapidly changing market for smart mobile phones, newways of consuming information is needed. In this master thesis project aPortable Document Format (PDF) viewer with more features than existingPDF viewers for Symbian^3 was developed, called PDF Eagle. PDF Eaglewas implemented using the Qt framework, allowing it to be easily ported todierent platforms. PDF documents have a rich structure and to be fullycompatible with the standard and at the same time responsive enough to berun on a mobile platform is a formidable technical challenge. This reportdescribes the issues that had to be resolved all the way to a functioning "app"that was marketed on the Nokia market in October 2011 with a great success.Among the technical challenges was a way to correctly render coloured objectsin PDFs. A gradient is a way to colour an area in a PDF le. Results of testsshowed that PDF Eagle is more capable of handling gradients, shadows andencrypted PDF les compared to other mobile PDF viewers. The conclusion ofthis report is that PDF Eagle is on par with or outmatches other PDF viewerson the targeted platform. This work also shows the feasibility of incrementallydownloading the pages of a PDF le which provides a better user experienceby faster viewing.

Paper-based user manuals that provide assembly and disassembly instructions often do so with a combination of diagrams supported with textual information that clarifies how to perform the tasks. Mobile devices are emerging as a multimedia platform for providing on-demand training due to their portability. Mobile devices have limited screen size; as a result, the text instructions associated with the diagrams can produce clutter and occlusion on the screen. Also, too much information if fed through a single sensory channel (visual) may result in excessive cognitive load on the working memory of the human brain, thus hindering the learning process. In this work, two user studies were conducted to investigate the tradeoffs of using text, voice, and a combination of both modalities on the learning experience in a just-in-time mobile learning scenario. In such a scenario end-users are managing two very visual tasks at the same time; i.e., the primary task of carrying out the assembly/disassembly job and the secondary task of learning how to perform the task.

The recent advances in mobile computing devices and wireless networking produced the technical platform for multimedia services over thin mobile devices. Nowadays, we are witnessing an important growth in applications using thin mobile devices, such as social networks, virtual walkthrough, media streaming, and augmented reality (AR), just to mention a few. Most of these applications are based on the client-server architecture, however several studies showed that the client-server architecture suffers from various issues, such as the server bottleneck, latency and the lack of scalability. This led most of the systems to switch to the peer-to-peer (P2P)-like environment for its scalability and potential cost saving. P2P multimedia streaming over thin mobile devices-based classes of applications has known a significant growth during the last years. Although P2P video streaming over thin mobile devices received a great deal of attention, the application of 3D streaming over mobile devices was challenging mainly due to the limited mobile resources and capabilities, as well as the wireless medium limitations. Having 3D streaming over Mobile Ad hoc Networks (MANET) is considered more challenging given that the 3D streaming-based system has to deal with a dynamic environment resulting from nodes mobility, which may lead to route breakages and connection loss. Therefore, one of the major difficulties in 3D streaming over MANET is related to the supplying partner's strategy that aims at determining the most suitable source holding the required 3D data to stream it quickly and efficiently to the requesters. In this thesis, we propose our P2P based 3D streaming system which we refer to as MOSAIC as well as a suite of supplying partner strategy protocols for P2P 3D streaming over thin mobile devices. Our proposed suite of protocols selects the potential sources that have the relevant 3D data, based on a set of criteria such as the source location, the mobile device's available resources as well as its residual energy. We also proposed a multihop supplying partner selection protocol that takes into account the signal strength and the nodes mobility when streaming the relevant 3D data. The performance evaluation obtained to evaluate our MOSAIC system as well as our suite of protocols using an extensive set of NS2 simulation experiments, is then reported.

Along with the huge growth of mobile devices in recent years we have seen a matching growth in interest for mobile applications, with location-aware applications experiencing rapid growth for mobile devices. Radiolocation from measurements of radio received signal strength has demonstrated excellent precision, although despite a decade of research there have been no wide-spread deployments of indoor location systems. The majority of the existing research has been focused towards producing improved precision at the cost of increased time requirements for system configuration and maintenance. This thesis proposes taking a step back from increasing complexity by giving up precision in exchange for simplicity and speed of deployment, while still providing sufficient accuracy for many indoor location tasks. This is accomplished by putting aside the standard x, y, z coordinate systems and by using a method based on defined areas. Carefully choosing the defined areas to include Wi-Fi access points and to have signal attenuating walls separating the area from the next, this work demonstrates locational accuracy of over 90% in most cases. While this method is not applicable to wide open areas that lack signal attenuating features, it is highly applicable to many indoor environments. / Graduate

Edge-cloud brings the computation power as close to the clients as possible. This reduces latencies and overall computation time in the cloud. Thanks to the mobile nature of clients we must be able to migrate tasks among different servers. The goal of this thesis is to examine possible problems in communication and propose the architecture of framework. Our framework uses gRPC and is written as module to it. It is platform independent, uses reliable communication and focuses on easy usage. We provide implementation of this framework with some example uses. 1