Preserving user privacy in pervasive environments with a collaborative model

Privacy is the most often cited criticism of context awareness in pervasive environments. Context aware pervasive applications have the vulnerabilities of capturing extensive portions of users' activities. Whether such data capture is an actual threat or not, users' perceptions of such possibilities may discourage them from using many useful pervasive applications. So far, in context aware pervasive applications, location data has been the main focus to make users anonymous. However in reality, user anonymity depends on all the privacy sensitive data collected by a particular application. Preserving user privacy or in other words, protecting user anonymity with the help of an anonymizer has the susceptibility of a single point of failure. In this paper, we propose a Formal Collaborative Model (FCM) that preserves users' anonymity without an anonymizer. This model can also quantify the amount of privacy at stake at the time of asking for services from untrustworthy service providers. Since our model can quantify service requester's achieved privacy when a request is going to be placed, it allows the users to be aware of their overall privacy preference situation in a pervasive environment.