Local Suppression and Splitting Techniques for Privacy Preserving Publication of Trajectories | IEEE Journals & Magazine | IEEE Xplore

Local Suppression and Splitting Techniques for Privacy Preserving Publication of Trajectories


Abstract:

We study the problem of preserving user privacy in the publication of location sequences. Consider a database of trajectories, corresponding to movements of people, captu...Show More

Abstract:

We study the problem of preserving user privacy in the publication of location sequences. Consider a database of trajectories, corresponding to movements of people, captured by their transactions when they use credit cards, RFID debit cards, or NFC (http://en.wikipedia.org/wiki/Near_field_communication) compliant devices. We show that, if such trajectories are published exactly (by only hiding the identities of persons that followed them), one can use partial trajectory knowledge as a quasi-identifier for the remaining locations in the sequence. We devise four intuitive techniques, based on combinations of locations suppression and trajectories splitting, and we show that they can prevent privacy breaches while keeping published data accurate for aggregate query answering and frequent subsets data mining.
Published in: IEEE Transactions on Knowledge and Data Engineering ( Volume: 29, Issue: 7, 01 July 2017)
Page(s): 1466 - 1479
Date of Publication: 01 March 2017

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