M. Tech. (Department of Information and Communication Technology, Faculty of Applied and Computer Sciences) Vaal University of Technology. / Mobile phone recommendation systems are of great importance for mobile operators to achieve a profit. In a user-derived market, the number of contract users and contract phones is especially significant for mobile service operators. The tremendous growth in the number of available mobile cellular telephone contracts necessitates the need for a recommender system to help users discover suitable contracts on the basis of their usage patterns. Recommender systems recommend items to users and their primary purpose is to increase sales and recommend items that are predicted to be suitable for individual users. There are two commonly used techniques in developing recommender systems including collaborative- and content-based filtering. Recommender systems make their recommendations based on data that is available on the system. These systems have gained popularity over the years and they have been adopted in many domains. In this study a recommender system for mobile subscriber provisioning was developed using a hybrid J48 and kmeans algorithms. The J48 algorithm was used for classifying subscribers per usage stream and then k-means was used to cluster all the subscribers of similar usage patterns. The algorithms were selected after being compared with other algorithms and the two performed best in their categories. The clustering algorithm, k-means, was able to cluster the sample data as follows: Cluster 0 contained 48% (1621) of the subscribers cluster 1 contained 42% (1423) subscribers, cluster 2 contained 8% (272) subscribers and lastly cluster 3 contained 74 subscribers representing 2% of the population and the run time of k-means is faster than that of EM. The classification algorithm j48 performed at an average of 99.98% for correctly classifying instances and this was higher than the Naïve Bayes, zeroR and MLP algorithms. The developed recommender system was able to successfully recommend contract packages to subscribers. A precision-recall curve was produced, and it showed good performance of the system. This study successfully highlighted the challenges in recommender systems, and showed that a hybrid system was better able to recommend products to the mobile subscribers.

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<p>Mobile systems, such as smartphones, wearables (e.g., smartwatches, AR/VR headsets),<br> and IoT devices, have come a long way from being just a method of communication to<br> sophisticated sensing devices that monitor and control several aspects of our lives. These<br> devices have enabled several useful applications in a wide range of domains ranging from<br> healthcare and finance to energy and agriculture industries. While such advancement has<br> enabled applications in several aspects of human life, it has also made these devices an<br> interesting target for adversaries.<br> In this dissertation, I specifically focus on how the various sensors on mobile devices can<br> be exploited by adversaries to violate users’ privacy and present methods to use sensors<br> to improve the security of these devices. My thesis posits that multi-modal sensing can be<br> leveraged to enhance the security and privacy of mobile systems.<br> In this, first, I describe my work that demonstrates that human interaction with mobile de-<br> vices and their accessories (e.g., stylus pencils) generates identifiable patterns in permissionless<br> mobile sensors’ data, which reveal sensitive information about users. Specifically, I developed<br> S3 to show how embedded magnets in stylus pencils impact the mobile magnetometer sensor<br> and can be exploited to infer a users incredibly private handwriting. Then, I designed LocIn<br> to infer a users indoor semantic location from 3D spatial data collected by mixed reality<br> devices through LiDAR and depth sensors. These works highlight new privacy issues due to<br> advanced sensors on emerging commodity devices.<br> Second, I present my work that characterizes the threats against smartphone authentication<br> and IoT device pairing and proposes usable and secure methods to protect against these threats.<br> I developed two systems, FaceRevelio and IoTCupid, to enable reliable and secure user and<br> device authentication, respectively, to protect users’ private information (e.g., contacts,<br> messages, credit card details) on commodity mobile and allow secure communication between<br> IoT devices. These works enable usable authentication on diverse mobile and IoT devices<br> and eliminate the dependency on sophisticated hardware for user-friendly authentication.</p>

Indiana University-Purdue University Indianapolis (IUPUI) / Component-Based Software Development (CSBD) has gained widespread importance in recent times, due to its wide-scale applicability in software development. System developers can now pick and choose from the pre-existing components to suit their requirements in order to build their system. For the purpose of developing a quality-aware system, finding the suitable components offering services is an essential and critical step. Hence, Service Discovery is an important step in the development of systems composed from already existing quality-aware software services. Currently, there is a plethora of new-age devices, such as PDAs, and cell phones that automate daily activities and provide a pervasive connectivity to users. The special characteristics of these devices (e.g., mobility, heterogeneity) make them as attractive choices to host services. Hence, they need to be considered and integrated in the service discovery process. However, due to their limitations of battery life, intermittent connectivity and processing capabilities this task is not a simple one. This research addresses this challenge of including resource constrained devices by enhancing the UniFrame Resource Discovery System (URDS) architecture. This enhanced architecture is called Mobile Device Enabled Service Discovery System (MDE-URDS). The experimental validation of the MDE-URDS suggests that it is a scalable and quality-aware system, handling the limitations of mobile devices using existing and well established algorithms and protocols such as Mobile IP.

Indiana University-Purdue University Indianapolis (IUPUI) / This work analyzes and discusses the current security environment of today's (and future) smartphones, and proposes a security model which will reduce smartphone vulnerabilities, preserving privacy, integrity and availability of smartphone native applications to authorized parties. For this purpose, we begin with an overlook of current smartphone security standards, and explore the threats, vulnerabilities and attacks on them, that have been uncovered so far with existing popular smartphones. We also look ahead at the future uses of the smartphones, and the security threats that these newer applications would introduce. We use this knowledge to construct a mathematical model, which gives way to policies that should be followed to secure the smartphone under the model. We finally discuss existing and proposed security mechanisms that can be incorporated in the smartphone architecture to meet the set policies, and thus the set security standards.

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With the advances in wireless communication technology and advanced positioning systems, a variety of Location-Based Services (LBS) become available to the public. Mobile users can issue location-based queries to probe their surrounding environments. One important type of query in LBS is moving monitoring queries over mobile objects. Due to the high frequency in location updates and the expensive cost of continuous query processing, server computation capacity and wireless communication bandwidth are the two limiting factors for large-scale deployment of moving object database systems. To address both of the scalability factors, distributed computing has been considered. These schemes enable moving objects to participate as a peer in query processing to substantially reduce the demand on server computation, and wireless communications associated with location updates. In the first part of this dissertation, we propose a distributed framework to process moving monitoring queries over moving objects in a spatial network environment. In the second part of this dissertation, in order to reduce the communication cost, we leverage both on-demand data access and periodic broadcast to design a new hybrid distributed solution for moving monitoring queries in an open space environment. Location-based services make our daily life more convenient. However, to receive the services, one has to reveal his/her location and query information when issuing locationbased queries. This could lead to privacy breach if these personal information are possessed by some untrusted parties. In the third part of this dissertation, we introduce a new privacy protection measure called query l-diversity, and provide two cloaking algorithms to achieve both location kanonymity and query l-diversity to better protect user privacy. In the fourth part of this dissertation, we design a hybrid three-tier architecture to help reduce privacy exposure. In the fifth part of this dissertation, we propose to use Road Network Embedding technique to process privacy protected queries.

We are witnessing exponential growth in the number of powerful, multiply-connected, energy-rich stationary and mobile nodes, which will make available a massive pool of computing and communication resources. We claim that cloud computing can provide resilient on-demand computing, and more effective and efficient utilization of potentially infinite array of resources. Current cloud computing systems are primarily built using stationary resources. Recently, principles of cloud computing have been extended to the mobile computing domain aiming to form local clouds using mobile devices sharing their computing resources to run cloud-based services. However, current cloud computing systems by and large fail to provide true on-demand computing due to their lack of the following capabilities: 1) providing resilience and autonomous adaptation to the real-time variation of the underlying dynamic and scattered resources as they join or leave the formed cloud; 2) decoupling cloud management from resource management, and hiding the heterogeneous resource capabilities of participant nodes; and 3) ensuring reputable resource providers and preserving the privacy and security constraints of these providers while allowing multiple users to share their resources. Consequently, systems and consumers are hindered from effectively and efficiently utilizing the virtually infinite pool of computing resources. We propose a platform for mobile cloud computing that integrates: 1) a dynamic real-time resource scheduling, tracking, and forecasting mechanism; 2) an autonomous resource management system; and 3) a cloud management capability for cloud services that hides the heterogeneity, dynamicity, and geographical diversity concerns from the cloud operation. We hypothesize that this would enable 'Collaborative Computing Cloud (C3)' for on-demand computing, which is a dynamically formed cloud of stationary and/or mobile resources to provide ubiquitous computing on-demand. The C3 would support a new resource-infinite computing paradigm to expand problem solving beyond the confines of walled-in resources and services by utilizing the massive pool of computing resources, in both stationary and mobile nodes. In this dissertation, we present a C3 management platform, named PlanetCloud, for enabling both a new resource-infinite computing paradigm using cloud computing over stationary and mobile nodes, and a true ubiquitous on-demand cloud computing. This has the potential to liberate cloud users from being concerned about resource constraints and provides access to cloud anytime and anywhere. PlanetCloud synergistically manages 1) resources to include resource harvesting, forecasting and selection, and 2) cloud services concerned with resilient cloud services to include resource provider collaboration, application execution isolation from resource layer concerns, seamless load migration, fault-tolerance, the task deployment, migration, revocation, etc. Specifically, our main contributions in the context of PlanetCloud are as follows. 1. PlanetCloud Resource Management • Global Resource Positioning System (GRPS): • Global mobile and stationary resource discovery and monitoring. A novel distributed spatiotemporal resource calendaring mechanism with real-time synchronization is proposed to mitigate the effect of failures occurring due to unstable connectivity and availability in the dynamic mobile environment, as well as the poor utilization of resources. This mechanism provides a dynamic real-time scheduling and tracking of idle mobile and stationary resources. This would enhance resource discovery and status tracking to provide access to the right-sized cloud resources anytime and anywhere. • Collaborative Autonomic Resource Management System (CARMS): Efficient use of idle mobile resources. Our platform allows sharing of resources, among stationary and mobile devices, which enables cloud computing systems to offer much higher utilization, resulting in higher efficiency. CARMS provides system-managed cloud services such as configuration, adaptation and resilience through collaborative autonomic management of dynamic cloud resources and membership. This helps in eliminating the limited self and situation awareness and collaboration of the idle mobile resources. 2. PlanetCloud Cloud Management Architecture for resilient cloud operation on dynamic mobile resources to provide stable cloud in a continuously changing operational environment. This is achieved by using trustworthy fine-grained virtualization and task management layer, which isolates the running application from the underlying physical resource enabling seamless execution over heterogeneous stationary and mobile resources. This prevents the service disruption due to variable resource availability. The virtualization and task management layer comprises a set of distributed powerful nodes that collaborate autonomously with resource providers to manage the virtualized application partitions. / Ph. D.

How people create and use information scraps, the small informal messages that people write to themselves to help them complete a task or remember something, has changed rapidly in the age of mobile computing. As recently as 2008, information scraps had continued to resist technological support. Since then, however, people have adopted mobile connected devices at a rate unimagined in the pre-smartphone era. Developers have, in turn, created a varied and growing body of smartphone software that supports many common information scrap use-cases. In this thesis, we describe our research into how and why people have adopted smartphone technology to serve their information scrap needs. The results of our survey show broad adoption of smartphones for many common information scrap tasks, particularly ones involving prospective memory. In addition, the results of our diary studies show that mobile contexts or locations are highly correlated with people's choosing to use smartphones to record information scraps. Our analysis of our diary study data also provides fresh understanding of the information scrap lifecycle and how mobile digital technology affects it. We find people's smartphone information scraps tend toward automatic archival, and we find their information scraps in general tend toward substantial role overlap regardless of medium. We use these findings to formulate a new information scrap lifecycle that is inclusive of mobile technology. These insights will help mobile technology creators to better support information scraps, which, in turn will allow users to enjoy the huge benefits of digital technology in their information scrap tasks. / Master of Science

Yes / A new generation of satellite systems that support regenerative on-board processors (OBPs) and multiple spot beam technology have opened new and efficient possibilities of implementing IP multicast communication over satellites. These new features have widened the scope of satellite-based applications and also enable satellite operators to efficiently utilize their allocated bandwidth resources. This makes it possible to provide cost effective satellite network services. IP multicast is a network layer protocol designed for group communication to save bandwidth resources and reduce processing overhead on the source side. The inherent broadcast nature of satellites, their global coverage (air, land, and sea), and direct access to a large number of subscribers imply satellites have unrivalled advantages in supporting IP multicast applications. IP mobility support in general and IP mobile multicast support in particular on mobile satellite terminals like the ones mounted on long haul flights, maritime vessels, continental trains, etc., still remain big challenges that have received very little attention from the research community. This paper proposes how Proxy Mobile IPv6 (PMIPv6)-based IP multicast mobility support defined for terrestrial networks can be adopted and used to support IP mobile multicast in future satellite networks, taking cognizance of the trend in the evolution of satellite communications.