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Today’s smartphone operating systems fail to provide users with adequate control and visibility into how third-party applications use their private data. We present TaintDroid, an efficient, system-wide dynamic taint tracking and analysis system for the popular Android platform that can

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We describe a platform for context-aware computing which enables applications to follow mobile users as they move around a building. The platform is particularly suitable for richly equipped, networked environments. The only item a user is required to carry is a small sensor tag, which identifies

In this paper we show that application-aware adaptation, a collaborative partnership between the operating system and applications, offers the most general and effective approach to mobile information access. We describe the design of Odyssey, a prototype implementing this approach, and show how

Context-enabled applications are just emerging and promise richer interaction by taking environmental context into account. However, they are difficult to build due to their distributed nature and the use of unconventional sensors. The concepts of toolkits and widget libraries in graphical user

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We describe an operating system architecture that securely multiplexes machine resources while permitting an unprecedented degree of application-specific customization of traditional operating system abstractions. By abstracting physical hardware resources, traditional operating systems have

Computing devices and applications are now used beyond the desktop, in diverse environments, and this trend toward ubiquitous computing is accelerating. One challenge that remains in this emerging research field is the ability to enhance the behavior of any application by informing

This article presents a measure of semantic similarityinanis-a taxonomy based on the notion of shared information content. Experimental evaluation against a benchmark set of human similarity judgments demonstrates that the measure performs better than the traditional edge-counting approach. The article presents algorithms that take advantage of taxonomic similarity in resolving syntactic and semantic ambiguity, along with experimental results demonstrating their e#ectiveness. 1. Introduction Evaluating semantic relatedness using network representations is a problem with a long history in arti#cial intelligence and psychology, dating back to the spreading activation approach of Quillian #1968# and Collins and Loftus #1975#. Semantic similarity represents a special case of semantic relatedness: for example, cars and gasoline would seem to be more closely related than, say, cars and bicycles, but the latter pair are certainly more similar. Rada et al. #Rada, Mili, Bicknell, & Blett...