f-Slip: an efficient privacy-preserving data publishing framework for 1:M microdata with multiple sensitive attributes
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s00500-021-06275-2.pdf
Reference37 articles.
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3. Adeel A, Nayma F, Saif URM, Mansoor A, Abid K, Moneeb G (2018b) An effective privacy preserving mechanism for 1: M microdata with high utility. Sustain Cities Soc 45:1–22. https://doi.org/10.1016/j.scs.2018.11.037
4. Ashwin M, Daniel K, Johannes G, Muthuramakrishnan V (2006) L-diversity: privacy beyond k-anonymity. ACM Trans Knowl Discov Data 1:1–52. https://doi.org/10.1145/1217299.1217302
5. Athanasios Z, Fran C, Agusti S, Constantinos P (2020) A survey on privacy properties for data publishing of relational data. IEEE Access. https://doi.org/10.1109/ACCESS.2020.2980235
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