Abstract
The increasing availability of data due to the explosion of mobile devices and positioning technologies has led to the development of efficient management and mining techniques for mobility data. However, the analysis of such data may result in significant risks regarding individuals’ privacy. A typical approach for privacy-aware mobility data sharing aims at publishing an anonymized version of the mobility dataset, operating under the assumption that most of the information in the original dataset can be disclosed without causing any privacy violation. On the other hand, an alternative strategy considers that data stays in-house to the hosting organization and privacy-preserving mobility data management systems are in charge of privacy-aware sharing of the mobility data. In this chapter, we present the state-of-the-art of the latter approach, including systems such as HipStream, Hermes++, and Private-Hermes.
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Kopanaki, D., Pelekis, N., Theodoridis, Y. (2018). Systems for Privacy-Preserving Mobility Data Management. In: Gkoulalas-Divanis, A., Bettini, C. (eds) Handbook of Mobile Data Privacy . Springer, Cham. https://doi.org/10.1007/978-3-319-98161-1_11
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