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A number of mobile applications have emerged that allow users to locate one another. However, people have expressed concerns about the privacy implications associated with this class of software, suggesting that broad adoption may only happen to the extent that these concerns are adequately addressed. In this article, we report on our work on PeopleFinder,(More)
* Primary contact point (sadeh@cs.cmu.edu) Abstract Over the past few years, a number of mobile applications have emerged that allow users to locate one another. Some of these applications are driven by a desire from enterprises to increase the productivity of their employees. Others are geared towards supporting social networking scenarios or(More)
We study methods of efficiently leveraging massive textual corpora through n-gram statistics. Specifically, we explore algorithms that use a database of frequency counts for sequences of tokens in a teraword Web corpus to correct spelling mistakes and to extract a list of instances of some category given only the name of the target category. For spelling(More)
We describe our current work in developing novel mechanisms for managing security and privacy in pervasive computing environments. More specifically, we have developed and evaluated three different applications, including a contextual instant messenger, a people finder application, and a phone-based application for access control. We also draw out some(More)
We study the problem of correcting spelling mistakes in text using memory-based learning techniques and a very large database of token n-gram occurrences in web text as training data. Our approach uses the context in which an error appears to select the most likely candidate from words which might have been intended in its place. Using a novel correction(More)
Google Chrome has implemented a number of “HTML5” APIs, including the Geolocation API and various storage APIs. In this paper we discuss some of our experiences on the Google Chrome team in implementing these APIs, as well as our thoughts around privacy for new APIs we are considering implementing. Specifically, we discuss our ideas of how providing access(More)
Phishing websites are a form of mimicking the legitimate ones for the purpose of stealing user 's confidential information such as usernames, passwords and credit card information. Recently machine learning and data mining techniques have been a promising approach for detection of phishing websites by distinguishing between phishing and legitimate(More)
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