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Nowadays, access to location-based services (LBSs) is becoming a central part of our daily life activities. For example, mobile phone users in Participatory sensing (PS) systems are requested to collect information from their nearby data collection points (DCs). A query typically reveals the identity and other personal information such as location, user profiles (e.g., race) and time. This knowledge...
Mobile phone users in Participatory sensing (PS) systems are requested to collect information from their nearby locations. To ensure accurate results this exercise is well ordered and coordinated with mobile objects assigned to collect data in each data collection point. The users location information should be concealed all the times. Several techniques in PS have been proposed recently to provide...
In the era of big data, the Privacy Preserving Data Mining (PPDM) technology is increasingly important. The aim is to dig out the hidden, previously unknown and potentially useful knowledge or pattern under the premise of protecting sensitive data. In this paper, we summarize the existing PPDM technology as well as its advantages and disadvantages. We combine distributed randomization with the K-anonymity...
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