We present our ongoing work on user data and contextual privacy preservation in mobile devices through semantic reasoning. Recent advances in context modeling, tracking and collaborative localization have led to the emergence of a new class of smartphone applications that can access and share embedded sensor data. Unfortunately, this also means significant amount of user context information is now accessible to applications and potentially others, creating serious privacy and security concerns. Mobile OS frameworks like Android lack mechanisms for dynamic privacy control. We show how data flow among applications can be successfully filtered at a much more granular level using semantic web driven technologies that model device location, surroundings, application roles as well as context-dependent information sharing policies.

Contemporary smartphones are capable of generating and transmitting large amounts of data about their users. Recent advances in collaborative context modeling combined with a lack of adequate permission model for handling dynamic context sharing on mobile platforms have led to the emergence of a new class of mobile applications that can access and share embedded sensor and context data. Most of the time such data is used for providing tailored services to the user but it can lead to serious breaches of privacy. We use Semantic Web technologies to create a rich notion of context. We also discuss challenges for context aware mobile platforms and present approaches to manage data flow on these devices using semantically rich fine-grained context-based policies that allow users to define their privacy and security need using tools we provide.

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Nature of the resource pool in a Grid environment is heterogeneous and dynamic. Availability, load and status of the resources may change at the time of execution of an application. Therefore, in order to maintain the performance guarantee (as has been agreed upon through service level agreements (SLAs) between the client and the resource providers), an application may need to adapt to its run-time environment on the basis of resource availability and application demands. Often it may be required to migrate the application components to a new set of resources during their execution so that performance guar- A. antee can be maintained. Objective of this paper is to present an adaptive execution scheme for achieving guaranteed performance on the basis of the SLAs. The scheme has been implemented based on the notion of performance properties and by deploying a set of autonomous agents within an integrated performance-based resource management framework.

Contemporary smartphones are capable of generating and transmitting large amounts of data about their users. Recent advances in collaborative context modeling combined with a lack of adequate permission model for handling dynamic context sharing on mobile platforms have led to the emergence of a new class of mobile applications that can access and share embedded sensor and context data. Most of the time such data is used for providing tailored services to the user but it can lead to serious breaches of privacy. We use Semantic Web technologies to create a rich notion of context. We also discuss challenges for context aware mobile platforms and present approaches to manage data flow on these devices using semantically rich fine-grained context-based policies that allow users to define their privacy and security need using tools we provide.