Pramod Jagtap

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—Recent years have seen a confluence of two major trends – the increase of mobile devices such as smart phones as the primary access point to networked information and the rise of social media platforms that connect people. Their convergence supports the emergence of a new class of context-aware geosocial networking applications. While existing systems(More)
We describe work on representing and using a rich notion of context that goes beyond current networking applications fo-cusing mostly on location. Our context model includes location and surroundings, the presence of people and devices, inferred activities and the roles people fill in them. A key element of our work is the use of collaborative information(More)
—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(More)
— The balance between privacy and security concerns is a hotly debated topic, especially as government (and private) entities are able to gather and analyze data from several disparate sources with ease. This ability to do large scale analytics of publicly accessible data leads to significant privacy concerns. In particular, for the government, there is the(More)
—A Cyber-Physical System (CPS) involves a tight coupling between the physical and computational elements. Security is a key challenge for the deployment of CPS. Therefore, it is highly desirable to extract correct information from a large volume of noisy data and properly evaluate the reputation of reporting devices in CPS. In this paper, we propose a(More)
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