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Advances in distributed service-oriented computing and global communications have formed a strong technology push for large-scale data integration among organizations and enterprises. However, concerns about data privacy become increasingly important for large-scale mission-critical data integration applications. Ideally, given a database query spanning multiple private databases, the authors wished...
Securing data is becoming a crucial need for most Internet-based applications. Whereas the problem of data confidentiality has been widely investigated, the problem of how to ensure that data, when moving among different parties, are modified only according to the stated policies has been so far not deeply investigated. In this paper, the authors proposed an approach supporting parallel and distributed...
One of the most notable challenges threatening the successful deployment of sensor systems is privacy. Although many privacy-related issues can be addressed by security mechanisms, one sensor network privacy issue that cannot be adequately addressed by network security is source-location privacy. Adversaries may use RF localization techniques to perform hop-by-hop traceback to the source sensor's...
This paper describes a personalized k-anonymity model for protecting location privacy against various privacy threats through location information sharing. Our model has two unique features. First, we provide a unified privacy personalization framework to support location k-anonymity for a wide range of users with context-sensitive personalized privacy requirements. This framework enables each mobile...
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