Private Frequent Itemset Mining in the Local Setting-Reference-Cited by-同舟云学术

Private Frequent Itemset Mining in the Local Setting

Published:2021 Issue: Volume: Page:338-350
ISSN:0302-9743
Container-title:Wireless Algorithms, Systems, and Applications
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Author:

Fu Hang,Yang Wei,Huang Liusheng

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-86130-8_27

Reference16 articles.

1. Frequent itemset mining dataset repository. http://fimi.ua.ac.be/data/

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3. Agrawal, R., Srikant, R.: Fast algorithms for mining association rules in large databases. In: Proceedings of 20th International Conference on Very Large Data Bases, pp. 487–499 (1994)

4. Alvim, M.S., Chatzikokolakis, K., Palamidessi, C., Pazii, A.: Metric-based local differential privacy for statistical applications. CoRR (2018). http://arxiv.org/abs/1805.01456

5. Andrés, M.E., Bordenabe, N.E., Chatzikokolakis, K., Palamidessi, C.: Geo-indistinguishability: differential privacy for location-based systems. In: 2013 ACM SIGSAC Conference on Computer and Communications Security, CCS 2013, Berlin, Germany, 4–8 November 2013, pp. 901–914 (2013)

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