In Chap. 3 we presented a mechanism for dealing with anonymising lossy data with low information loss, and without putting privacy at risk. Chap. 4 built on the discussion in Chap. 3 , to look in depth at the issue of efficient quasi-identifier discovery as a means of guaranteeing privacy. As we mentioned in Chap. 2 , quasi-identifier discovery is central to enabling syntactic data anonymisation and is particularly relevant in scenarios that involve compositions of large datasets emanating from multiple (independent) distributed data owners.

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Accounting for User Privacy Preferences

  • Anne V. D. M. Kayem

摘要

In Chap. 3 we presented a mechanism for dealing with anonymising lossy data with low information loss, and without putting privacy at risk. Chap. 4 built on the discussion in Chap. 3 , to look in depth at the issue of efficient quasi-identifier discovery as a means of guaranteeing privacy. As we mentioned in Chap. 2 , quasi-identifier discovery is central to enabling syntactic data anonymisation and is particularly relevant in scenarios that involve compositions of large datasets emanating from multiple (independent) distributed data owners.